Optimal method and apparatus for neural modulation for the treatment of neurological disease, particularly movement disorders

ABSTRACT

A neurological control system for modulating activity of any component or structure comprising the entirety or portion of the nervous system, or any structure interfaced thereto, generally referred to herein as a “nervous system component.” The neurological control system generates neural modulation signals delivered to a nervous system component through one or more intracranial (IC) stimulating electrodes in accordance with treatment parameters. Such treatment parameters may be derived from a neural response to previously delivered neural modulation signals sensed by one or more sensors, each configured to sense a particular characteristic indicative of a neurological or psychiatric condition. Neural modulation signals include any control signal which enhances or inhibits cell activity. Significantly the neurological control system considers neural response, in the form of the sensory feedback, as an indication of neurological disease state and/or responsiveness to therapy, in the determination of treatment parameters.

RELATED APPLICATIONS

[0001] This application claims the benefit of prior and co-pending U.S.patent application Ser. No. 09/340,326, entitled APPARAUS AND METHOD FORCLOSED-LOOP INTRACRANIAL STIMULATION FOR OPTIMAL CONTROL OF NEUROLOGICALDISEASE, filed Jun. 25, 1999, and naming as inventor Daniel JohnDiLorenzo, and to U.S. Provisional Patent Application No. 60/095,413,entitled OPTIMAL METHOD AND APPARATUS FOR NEURAL MODULATION FOR THETREATMENT OF NEUROLOGICAL DISEASE, PARTICULARLY MOVEMENT DISORDERS,filed Aug. 5, 1998, also naming as inventor Daniel John DiLorenzo.

BACKGROUND OF THE INVENTION

[0002] 1. Field of the Invention

[0003] The present invention relates generally to neurological diseaseand, more particularly, to intracranial stimulation for optimal controlof movement disorders and other neurological disease.

[0004] 2. Related Art

[0005] There are a wide variety of treatment modalities for neurologicaldisease including movement disorders such as Parkinson's Disease,Huntington's Disease, and Restless Leg Syndrome, as well as psychiatricdisease including depression, bipolar disorder and borderlinepersonality disorders. These treatment modalities are moderatelyefficacious; however, they suffer from sever severe drawbacks. Each ofthese traditional treatment modalities and their associated limitationsare described below.

[0006] One common conventional technique for controlling neurologicaldisease includes the use of dopaminergic agonists or anticholinerigicagents. Medical management using these techniques requires considerableiteration in dosing adjustments before an “optimal” balance betweenefficacy and side effect minimalization is achieved. Variation,including both circadian and postprandial variations, causes widefluctuation in symptomatology. This commonly results in alternationbetween “on” and “off” periods during which the patient possesses andloses motor functionality, respectively.

[0007] Another traditional approach for controlling movement disordersis tissue ablation. Tissue ablation is most commonly accomplishedthrough stereotactic neurosurgical procedures, including pallidotomy,thalamotomy, subthalamotomy, and other lesioning procedures. Theseprocedures have been found to be moderately efficatious. However, inaddition to posing risks that are inherent to neurosurgical operations,these procedures suffer from a number of fundamental limitations. Onesuch limitation is that tissue removal or destruction is irreversible.As a result, excessive or inadvertent removal of tissue cannot beremedied.

[0008] Furthermore, undesirable side effects, including compromise ofvision and motor or sensory functions, are likely to be permanentconditions. In particular, bilateral interventions place the patient atconsiderable risk for developing permanent neurologic side effects,including incontinence, aphasia, and grave psychic disorders. Anadditional drawback to this approach is that the “magnitude” oftreatment is constant. That is, it is not possible to vary treatmentintensity over time, as may be required to match circadian,postprandial, and other fluctuations in symptomatology and consequenttherapeutic needs. Thus, decrease in treatment “magnitude” is notpossible while an increase in treatment “magnitude” necessitatesreoperation. Some adjustment is possible through augmentation withpharmacologic treatment; however, these additional treatments aresubject to the above-noted limitations related to drug therapy.

[0009] Another traditional approach for controlling movement disordersand other neurological disease includes tissue transplantation,typically from animal or human mesencephalic cells. Although tissuetransplantation in humans has been performed for many years, it remainsexperimental and is limited by ethical concerns when performed using ahuman source. Furthermore, graft survival, as well as subsequentfunctional connection with intracranial nuclei, are problematic. Theyield, or percentage of surviving cells, is relatively small and is notalways predictable, posing difficulties with respect to the control oftreatment “magnitude.”

[0010] Another traditional approach for controlling neurological diseaseis the continuous electrical stimulation of a predetermined neurologicalregion. Chronic high frequency intracranial electrical stimulation istypically used to inhibit cellular activity in an attempt tofunctionally replicate the effect of tissue ablation, such aspallidotomy and thalamotomy. Acute electrical stimulation and electricalrecording and impedance measuring of neural tissue have been used forseveral decades in the identification of brain structures for bothresearch purposes as well as for target localization duringneurosurgical operations for a variety of neurological diseases. Duringintraoperative electrical stimulation, reduction in tremor has beenachieved using frequencies typically on the order of 75 to 330 Hz. Basedon these findings, chronically implanted constant-amplitude electricalstimulators have been implanted in such sites as the thalamus,subthalamic nucleus and globus pallidus.

[0011] Chronic constant-amplitude stimulation has been shown to bemoderately efficacious. However, it has also been found to be limited bythe lack of responsiveness to change in patient system symptomatologyand neuromotor function. Following implantation, a protracted phase ofparameter adjustment, typically lasting several weeks to months, isendured by the patient while stimulation parameters are interactivelyadjusted during a series of patient appointments. Once determined, an“acceptable” treatment magnitude is maintained as a constant stimulationlevel. A drawback to this approach is that the system is not responsiveto changes in patient need for treatment. Stimulation is typicallyaugmented with pharmacological treatment to accommodate such changes,causing fluctuation of the net magnitude of treatment with the plasmalevels of the pharmacologic agent.

[0012] As noted, while the above and other convention treatmentmodalities offer some benefit to patients with movement disorders, theirefficacy is limited. For the above-noted reasons, with such treatmentmodalities it is difficult and often impossible to arrive at an optimaltreatment “magnitude,” that is, an optimal dose or intensity oftreatment. Furthermore, patients are subjected to periods ofovertreatment and undertreatment due to variations in disease state.Such disease state variations include, for example, circadianfluctuations, postprandial (after meal) and nutrition variations,transients accompanying variations in plasma concentrations ofpharmacological agents, chronic progression of disease, and others.

[0013] Moreover, a particularly significant drawback to the above andother traditional treatment modalities is that they suffer frominconsistencies in treatment magnitude. For example, with respect todrug therapy, a decrease in responsiveness to pharmacologic agentseventually progresses to eventually preclude effective pharmacologictreatment. With respect to tissue ablation, progression of disease oftennecessitates reoperation to extend pallidotomy and thalamotomy lesiondimensions. Regarding tissue transplantation, imbalances between celltransplant formation rates and cell death rates cause unanticipatedfluctuations in treatment magnitude. For continuous electricalstimulation, changes in electrode position, electrode impedance, as wellas patient responsiveness to stimulation and augmentative pharmacologicagents, cause a change in response to a constant magnitude of therapy.

[0014] Currently, magnets commonly serve as input devices used bypatients with implantable stimulators, including deep brain stimulators,pacemakers, and spinal cord stimulators. Current systems require thepatient to manually turn the system off at night time to conservebattery power and use such magnets to maintain system power. Thispresents considerable difficulty to many patients whose tremorsignificantly impairs arm function, as they are unable to hold a magnetin a stable manner over the implanted electronics module. Consequently,many patients are unable to turn their stimulators on in the morningwithout assistance.

[0015] What is needed, therefore, is an apparatus and method fortreatment of patients with neurological disease in general and movementdisorders in particular that is capable of determining and providing anoptimal dose or intensity of treatment. Furthermore, the apparatus andmethod should be responsive to unpredictable changes in symptomatologyand minimize alternations between states of overtreatment andundertreatment. The system should also be capable of anticipating futurechanges in symptomatology and neuromotor functionality, and beingresponsive to such changes when the occur.

SUMMARY OF THE INVENTION

[0016] The present invention is a neurological control system formodulating activity of any component or structure comprising theentirety or portion of the nervous system, or any structure interfacedthereto, generally referred to herein as a “nervous system component.”The neurological control system generates neural modulation signalsdelivered to a nervous system component through one or more intracranial(IC) stimulating electrodes in accordance with treatment parameters.Such treatment parameters may be derived from a neural response topreviously delivered neural modulation signals sensed by one or moresensors, each configured to sense a particular characteristic indicativeof a neurological or psychiatric condition. Neural modulation signalsinclude any control signal which enhances or inhibits cell activity.Significantly the neurological control system considers neural response,in the form of the sensory feedback, as an indication of neurologicaldisease state and/or responsiveness to therapy, in the determination oftreatment parameters.

[0017] In one aspect of the invention, a neural modulation system foruse in treating disease which provides stimulus intensity which may bevaried is disclosed. The stimulation may be at least one of activating,inhibitory, and a combination of activating and inhibitory and thedisease is at least one of neurologic and psychiatric. For example, theneurologic disease may include Parkinson's disease, Huntington'sdisease, Parkinsonism, rigidity, hemiballism, choreoathetosis, dystonia,akinesia, bradykinesia, hyperkinesia, other movement disorder, epilepsy,or the seizure disorder. The psychiatric disease may include, forexample, depression, bipolar disorder, other affective disorder,anxiety, phobia, schizophrenia, multiple personality disorder. Thepsychiatric disorder may also include substance abuse, attention deficithyperactivity disorder, impaired control of aggression, or impairedcontrol of sexual behavior.

[0018] In another aspect of the invention, a neurological control systemis disclosed. The neurological control system modulates the activity ofat least one nervous system component, and includes at least oneintracranial stimulating electrode, each constructed and arranged todeliver a neural modulation signal to at least one nervous systemcomponent; at least one sensor, each constructed and arranged to senseat least one parameter, including but not limited to physiologic valuesand neural signals, which is indicative of at least one of diseasestate, magnitude of symptoms, and response to therapy; and a stimulatingand recording unit constructed and arranged to generate said neuralmodulation signal based upon a neural response sensed by said at leastone sensor in response to a previously delivered neural modulationsignal.

[0019] In another aspect of the invention, an apparatus for modulatingthe activity of at least one nervous system component is disclosed. Theapparatus includes means for delivering neural modulation signal to saidnervous system component; and means for sensing neural response to saidneural modulation signal. In one embodiment, the delivery meanscomprises means for generating said neural modulation signal, saidgenerating means includes signal conditioning means for conditioningsensed neural response signals, said conditioning including but notlimited to at least one of amplification, lowpass filtering, highpassfiltering, bandpass filtering, notch filtering, root-mean squarecalculation, envelope determination, and rectification; signalprocessing means for processing said conditioned sensed neural responsesignals to determine neural system states, including but not limited toa single or plurality of physiologic states and a single or plurality ofdisease states; and controller means for adjusting neural modulationsignal in response to sensed neural response to signal.

[0020] Advantageously, aspects of the neurological control system arecapable of incorporating quantitative and qualitative measures ofpatient symptomatology and neuromotor circuitry function in theregulation of treatment magnitude.

[0021] Another advantage of certain aspects of the present invention isthat it performs automated determination of the optimum magnitude oftreatment. By sensing and quantifying the magnitude and frequency oftremor activity in the patient, a quantitative representation of thelevel or “state” of the disease is determined. The disease state ismonitored as treatment parameters are automatically varied, and thelocal or absolute minimum in disease state is achieved as the optimalset of stimulation parameters is converged upon. The disease state maybe represented as a single value or a vector or matrix of values; in thelatter two cases, a multi variable optimization algorithm is employedwith appropriate weighting factors. Automated optimization of treatmentparameters expedites achievement of satisfactory treatment of thepatient, reducing the time and number of interactions, typically inphysician visits, endured by the patient. This optimization includesselection of electrode polarities, electrode configurations stimulatingparameter waveforms, temporal profile of stimulation magnitude,stimulation duty cycles, baseline stimulation magnitude, intermittentstimulation magnitude and timing, and other stimulation parameters.

[0022] Another advantage of certain aspects of the present invention isits provision of signal processed sensory feedback signals to cliniciansto augment their manual selection of optimum treatment magnitude andpattern. Sensory feedback signals provided to the clinician via aclinician-patient interface include but are not limited to tremorestimates, electromyography (EMG) signals, EEG signals, accelerometersignals, acoustic signals, peripheral nerve signals, cranial nervesignals, cerebral or cerebellar cortical signals, signals from basalganglia, signals from other brain or spinal cord structures, and othersignals.

[0023] A further advantage of certain aspects of the present inventionis that it provides modulation of treatment magnitude to compensate forpredictable fluctuations in symptomatology and cognitive and neuromotorfunctionality. Such fluctuations include those due to, for example, thecircadian cycle, postprandial and nutritional changes in symptomatology,and variations in plasma levels of pharmacologic agents.

[0024] A further advantage of certain aspects of the present inventionis that it is responsive to patient symptomatology, as tremor typicallyabates during sleep. This overcomes the above-noted problems of patientinability to hold a magnet in a stable manner over the implantedelectronics module and the resulting problem of not being able to turntheir stimulators on in the morning without assistance.

[0025] A still further advantage of certain aspects of the presentinvention is that it provides prediction of future symptomatology,cognitive and neuromotor functionality, and treatment magnituderequirements. Such predictions may be based on preset, learned andreal-time sensed parameters as well as input from the patient, physicianor other person or system.

[0026] A still further advantage of certain aspects of the presentinvention is that it optimizes the efficiency of energy used in thetreatment given to the patient. Stimulation intensity may be minimizedto provide the level of treatment magnitude necessary to control diseasesymptoms to a satisfactory level without extending additional energydelivering unnecessary overtreatment.

[0027] Further features and advantages of the present invention, as wellas the structure and operation of various embodiments of the presentinvention, are described in detail below with reference to theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention is described with reference to theaccompanying drawings. In the drawings, like reference numerals indicateidentical or functionally similar elements.

[0029]FIG. 1 is a schematic diagram of one embodiment of the presentinvention implanted bilaterally in a human patient.

[0030]FIG. 2 is an architectural block diagram of one embodiment of theneurological control system of the present invention.

[0031]FIG. 3 is a block diagram of one embodiment of an intracranialrecording electrode (ICRE) signal processor and an intracranialstimulating electrode (ICSE) signal processor each of which are includedwithin the signal processor illustrated in FIG. 2.

[0032]FIG. 4 is a schematic diagram of a globus pallidus implanted withstimulating and recording electrodes in accordance with one embodimentof the present invention.

[0033]FIG. 5 is a block diagram of one embodiment of an EMG signalprocessor which is included in one embodiment of the signal processorillustrated in FIG. 2.

[0034]FIG. 6 is a block diagram of one embodiment of an EEG signalprocessor module which is included in one embodiment of the signalprocessor illustrated in FIG. 2.

[0035]FIG. 7 is a block diagram of one embodiment of an accelerometersignal processor which is incorporated into certain embodiments of thesignal processor illustrated in FIG. 2.

[0036]FIG. 8 is a block diagram of one embodiment of an acoustic signalprocessor which is included in certain embodiments of the signalprocessor illustrated in FIG. 2.

[0037]FIG. 9 is block diagram of one embodiment of a peripheral nerveelectrode (PNE) signal processor 237 which is implemented in certainembodiments of signal processor 71. PNE signal

[0038]FIG. 10 is a schematic diagram of one embodiment of the signalprocessor illustrated in FIG. 2.

[0039]FIG. 11 is a schematic diagram of the patient-neural modulatorsystem illustrated in FIG. 2 illustrated to show its controller andobserver components.

[0040]FIG. 12 is a schematic diagram of one embodiment of the controlcircuit illustrated in FIG. 2.

[0041]FIG. 13 is a schematic diagram of electrical stimulation waveformsfor neural modulation.

[0042]FIG. 14 is a schematic diagram of one example of the recordedwaveforms.

[0043]FIG. 15 is a schematic block diagram of an analog switch used toconnect one or an opposing polarity pair of Zener diodes across thenoninverting and inverting inputs of an intracranial recording electrodeamplifier.

DETAILED DESCRIPTION

[0044]FIG. 1 is a schematic diagram of one embodiment of theintracranial stimulator of the present invention implanted bilaterallyin a human patient. In the embodiment illustrated in FIG. 1, twoneurological control systems 999 are shown implanted bilaterally. Eachsystem 999 includes a stimulating and recording unit 26 and one or moreintracranial components described below. As described in thisillustrative embodiment, the intracranial components preferably includea stimulating electrode array 37. However, it should become apparent tothose of ordinary skill in the relevant art after reading the presentdisclosure that the stimulating electrodes may also be extracranial;that is, attached to a peripheral nerve in addition to or in place ofbeing located within the cranium. As shown in FIG. 1, stimulating andrecording unit 26 of each neurological control system 999 is preferablyimplanted contralateral to the intracranial components of the device.

[0045] As one skilled in the relevant art would find apparent from thefollowing description, the configuration illustrated in FIG. 1 is justone example of the present invention. Many other configurations arecontemplated. For example, in alternative embodiments of the presentinvention, the stimulating and recording unit 26 is implantedipsilateral or bilateral to the intracranial components. It should alsobe understood that the stimulating and recording unit 26 can receiveipsilateral, contralateral or bilateral inputs from sensors and deliveripsilateral, contralateral, or bilateral outputs to a single or aplurality of intracranial stimulating electrode arrays 37. Preferably,these inputs are direct or preamplified signals from at least one of EMGelectrode array 50, EEG electrode array 51, Accelerometer Array 52,Acoustic Transducer Array 53, Peripheral Nerve Electrode Array 54, andIntracranial Recording Electrode Array 38. The signals input from thesesensors will be referred to herein as “sensory input modalities” 247.The outputs include but are not limited to one or more stimulatingcurrent signals or stimulating voltage signals to IntracranialStimulating Electrode Array 37.

[0046] In the embodiment illustrated in FIG. 1, the two unilateralsystems 26 are shown to receive sensory inputs from the sidecontralateral as well as the intracranial stimulating electrode arrays37. In the illustrative embodiment, systems 26 also receive sensoryinputs from intracranial recording electrode arrays 38. As will becomeapparent from the following description, intracranial recordingelectrode arrays 38 may provide valuable feedback information.

[0047] It should be understood that this depiction is for simplicityonly, and that any combination of ipsilateral, contralateral orbilateral combination of each of the multiple sensory input modalitiesand multiple stimulation output channels may be employed. In addition,stimulating and recording units 26 may be a single device, twocommunicating devices, or two independent devices. Accordingly, theseand other configurations are considered to be within the scope of thepresent invention. It is anticipated that stimulating and recordingunits 26, if implemented as distinct units, would likely be implanted inseparate procedures (soon after clinical introduction) to minimize thelikelihood of drastic neurological complications.

[0048] In the exemplary embodiment illustrated in FIG. 1, theintracranial stimulating electrode array 37 includes a plurality ofintracranial stimulating electrodes 1, 2, 3 and 4. Array 37 may, ofcourse, have more or fewer electrodes than that depicted in FIG. 1.These intracranial stimulating electrodes 1-4 may be used to providestimulation to a predetermined nervous system component. The electricalstimulation provided by the intracranial stimulating electrodes 1-4 maybe excitatory or inhibitory, and this may vary in a manner which ispreprogrammed, varied in real-time, computed in advance using apredictive algorithm, or determined using another technique now orlatter developed.

[0049] The intracranial recording electrode arrays 38 includesintracranial recording electrodes 5 and 6. In accordance with oneembodiment of the present invention, the intracranial recordingelectrodes 5, 6 are used to record cortical activity as a measure ofresponse to treatment and as a predictor of impeding treatment magnituderequirements. In the illustrative embodiment, intracranial recordingelectrodes 5 and 6 are depicted in a location superficial to theintracranial stimulating electrodes 1-4. However, this positioning maybe reversed or the intracranial stimulating electrodes 1-4 andintracranial recording electrodes 5 and 6 may be interspersed inalternative embodiments. For example, these electrodes may be placed inat least one of motor cortex, premotor cortex, supplementary motorcortex, other motor cortical areas, somatosensory cortex, other sensorycortical areas, Wernicke's area, Broca's area, other cortical region,other intracranial region, and other extracranial region.

[0050] In the illustrative embodiment, an intracranial catheter 7 isprovided to mechanically support and facilitate electrical connectionbetween intracranial and extracranial structures. In this embodiment,intracranial catheter 7 contains one or more wires connectingextracranial stimulating and recording circuit 26 to the intracranialelectrodes, including but not limited to, intracranial stimulatingelectrodes 1-4 and intracranial recording electrodes 5, 6. The wirescontained within intracranial catheter 7 transmit stimulating electrodeoutput signal (SEOS) to intracranial stimulating electrode array 37.Such wires additionally transmit stimulating electrode input signal(SEIS) and recording electrode input signal (REIS), from intracranialstimulating electrode array 37 and intracranial recording electrodearray 38 respectively, to stimulating and recording circuit 26.

[0051] Stimulating and recording circuit 26 is protected within acircuit enclosure 44. Circuit enclosure 44 and contained components,including stimulating and recording circuit 26 comprise stimulating andrecording unit 43. It should be understood that more or fewer of eithertype of electrode as well as additional electrode types and locationsmay be incorporated or substituted without departing from the spirit ofthe present invention. Furthermore, stimulating and recording circuit 26can be placed extra cranially in a subclavian pocket as shown in FIG. 1,or it may be placed in other extracranial or intracranial locations.

[0052] Connecting cable 8 generally provides electrical connectionbetween intracranial or intracranial locations. A set of electricalwires provides the means for communication between the intracranial andextracranial components; however, it should be understood that alternatesystems and techniques such as radiofrequency links, optical (includinginfrared) links with transcranial optical windows, magnetic links, andelectrical links using the body components as conductors, may be usedwithout departing from the present invention. Specifically, in theillustrative embodiment, connecting cable 8 provides electricalconnection between intracranial components 246 and stimulating andrecording circuit 26. In embodiments wherein stimulating and recordingcircuit 26 has an intracranial location, connecting cable 8 would likelybe entirely intracranial. Alternatively, connecting in embodimentswherein stimulating and recording circuit 26 is implanted under scalp 10or within or attached to calvarum 9, connecting cable 8 may be confinedentirely to subcutaneous region under the scalp 10.

[0053] A catheter anchor 29 provides mechanical connection betweenintracranial catheter 7 and calvarum 9. Catheter anchor 29 is preferablydeep to the overlying scalp 10. Such a subcutaneous connecting cable 8provides electrical connection between intracranial electrodes 246 andstimulating and recording circuit 26. Cable 8 may also connect any othersensors, including but not limited to any of sensory input modalities247, or other stimulating electrodes, medication dispensers, oractuators with stimulating and recording circuit 26.

[0054] Sensory feedback is provided to recording and stimulating unit 26from a multiplicity of sensors, collectively referred to as sensoryinput modalities 247. Intracranial recording electrode array 38,previously described, is intracranial in location. Additional sensors,most of which are located extracranially in the preferred embodiment,comprise the remainder of sensory input modalities 247. Sensory inputmodalities 247 provide information to stimulating and recording unit 26.As will be described in greater detail below, such information isprocessed by stimulating and recording unit 26 to deduce the diseasestate and progression and its response to therapy.

[0055] In one embodiment of the invention, a head-mounted acousticsensor 11 is used to monitor any number of vibratory characteristicssuch as high frequency head vibration, muscle vibration, and/or speechproduction. Head-mounted acoustic sensor 11 is connected to stimulatingand recording circuit 26 with an acoustic sensor connecting cable 30.

[0056] A head-mounted accelerometer 12 is implemented in certainembodiments of the present invention to monitor head movement andposition with respect to gravity. Head-mounted accelerometer 12 may bemounted to any structure or structures that enables it to accuratelysense a desired movement. Such structures include, for example, theskull base, calvarum, clavicle, mandible, extraocular structures, softtissues and vertebrae. Head-mounted accelerometer 12 is connected tostimulating and recording circuit 26 with an accelerometer connectingcable 31.

[0057] A proximal electromyography (EMG) electrode array 45 is alsoincluded in certain preferred embodiments of the invention. Proximal EMGelectrode array 45 includes a positive proximal EMG electrode 13, areference proximal EMG electrode 14, and a negative proximal EMGelectrode 15. As one skilled in the relevant art would find apparent,proximal EMG electrode array 45 may include any number of type ofelectrodes. Proximal EMG electrode array 45 is implanted in or adjacentto muscle tissue. In the embodiment illustrated in FIG. 1, proximal EMGelectrode array 45 is shown implanted within the neck of the humanpatient. However, it should be understood that this location isillustrative only and that proximal EMG electrode array 45 may beimplanted in or adjacent to any muscle without departing from the spiritof the present invention.

[0058] A proximal acoustic sensor 27 may also be implemented in thepresent invention. Proximal acoustic sensor 27 senses muscle vibrationand may be used to augment, supplement or replace EMG recording. Also, aproximal accelerometer 28 may be used to sense movement, includingtremor and voluntary activity, and orientation with respect to gravity.Proximal connecting cable 16 provides electrical connection from theproximal EMG electrodes 14 and 15, proximal acoustic sensor 27, andproximal accelerometer 28 to stimulating and recording circuit 26. Inthe illustrative embodiment, these sensors are shown connected to acommon proximal connecting cable 16. However, in alternativeembodiments, this configuration may include the use of multipleconnecting cables or implement other types of communication mediawithout departing from the present invention. It should also beunderstood from the preceding description that the number of each typeof sensor may also be increased or decreased, some sensor types may beeliminated, and other sensor types may be included without departingfrom the spirit of the present invention.

[0059] A distal EMG electrode array 47 may also be included in certainembodiments of the present invention. In such embodiments, distal EMGelectrode array 47 typically includes a positive distal EMG electrode17, a reference distal EMG electrode 42, and a negative distal EMGelectrode 18. Positive distal EMG electrode 17 is connected tostimulating and recording circuit 26 by positive distal EMG connectingcable 20. Negative distal EMG electrode 18 is connected to stimulatingand recording circuit 26 by negative distal EMG connecting cable 21.Reference distal EMG electrode 42 is connected to stimulating andrecording circuit 26 by reference distal EMG connecting cable 48.

[0060] In other embodiments, a distal acoustic sensor 19 is connected tostimulating and recording circuit 26 by distal acoustic connecting cable22. Distal accelerometer 33 is connected to stimulating and recordingcircuit 26 by distal accelerometer connecting cable 34. Distalaccelerometer 33 is connected to stimulating and recording circuit 26 bydistal accelerometer connecting cable 34.

[0061] In the embodiment illustrated in FIG. 1, distal EMG electrodearray 47, distal acoustic sensor 19, and distal accelerometer 33 areshown located in the shoulder region. However, the distal EMG electrodearray 47 may be located in other locations, including, for example, themasseter, temporalis, sternocleidomastoid, other portion of the head andneck, pectoralis, torso, abdomen, upper extremities, lower extremities,and other locations. The number of each type of sensor may be increasedor decreased, some sensor types may be eliminated, and other sensortypes may be included without departing from the spirit of the presentinvention.

[0062] An enclosure-mounted EMG electrode array 46 is illustrated inFIG. 1. Enclosure-mounted EMG electrode array 46 includesenclosure-mounted positive EMG electrode 23, enclosure-mounted negativeEMG electrode 24 and enclosure-mounted reference EMG electrode 25, allof which are attached to the circuit enclosure 44 that enclosesstimulating and recording unit 26. The circuit enclosure 44 ispreferably included to provide robustness against potential leadentanglement and fracture. In one particular embodiment, circuitenclosure 44 is constructed of titanium and epoxy, or other single orcombination of bio-compatible materials. Enclosure-mounted acousticsensor 35 and enclosure-mounted accelerometer 36 are mounted tostimulating and recording unit 43. The number of each type of sensor maybe increased or decreased, their locations changed, some sensor typeseliminated, and other sensor types included without departing from thespirit of the present invention.

[0063] In the embodiment illustrated in FIG. 1, EEG electrodes 39, 40,41 are provided. The EEG electrodes may be mounted directly toconnecting cable 8 or may be connected via intermediate cables. Any oneof the numerous standard and new electrode configurations, or montages,may be employed in EEG electrodes 39-41 without departing from thepresent invention.

[0064] In one embodiment, a proximal peripheral nerve electrode array 98is connected to stimulating and recording circuit 26 by proximalperipheral nerve electrode array connecting cable 100. Proximalperipheral nerve electrode array 98 is shown located in the neck region.In this location proximal peripheral nerve electrode array 98 caninterface with the vagus nerve, spinal accessory nerve, or nerve arisingfrom cervical roots.

[0065] A distal peripheral nerve electrode array 99 is connected tostimulating and recording circuit 26 by distal peripheral nerveelectrode array connecting cable 32. Distal peripheral nerve electrodearray 99 is shown located by the proximal arm, in position to interfacewith the brachial plexus or proximal arm nerve. One or more of theseperipheral nerve electrode arrays may be implanted in these or otherlocations, including but not limited to the head, cranial nerves, neck,torso, abdomen, upper extremities, and lower extremities, withoutdeparting from the present invention.

[0066] In one preferred embodiment, the peripheral nerve electrodearrays are each comprised of three epineural platinum-iridium ringelectrodes, each in with an internal diameter approximately 30% largerthan that of the epineurium, longitudinally spaced along the nerve.Electrodes of differing dimensions and geometries and constructed fromdifferent materials may alternatively be used without departing from thepresent invention. Alternative electrode configurations include but arenot limited to epineural, intrafascicular, or other intraneuralelectrodes; and materials include but are not limited to platinum, gold,stainless steel, carbon, and other element or alloy.

[0067]FIG. 2 is an architectural block diagram of one embodiment of theneurological control system 248 of the present invention for modulatingthe activity of at least one nervous system component in a patient. Asused herein, a nervous system component includes any component orstructure comprising an entirety or portion of the nervous system, orany structure interfaced thereto. In one preferred embodiment, thenervous system component that is controlled by the present inventionincludes the globus pallidus internus. In another preferred embodiment,the controlled nervous system component is the subthalamic nucleus.

[0068] The neurological control system 248 includes one or moreimplantable components 249 including a plurality of sensors eachconfigured to sense a particular characteristic indicative of aneurological or psychiatric condition. One or more intracranial (IC)stimulating electrodes in an IC stimulating electrode array 37 deliversa neural modulation signal to the same or other nervous system componentas that being monitored by the system 26. One or more sensors 38, 51,52, 53, and 54 sense the occurrence of neural responses to the neuralmodulation signals. Stimulating and recording unit 26 generates theneural modulation signal based on the neural response sensed by thesensors.

[0069] The neurological control system 248 preferably also includes apatient interface module 55 and a supervisory module 56. A controlcircuit 72 (described below) is communicably coupled to the patientinterface module 55 and receives signal inputs from and provides signaloutputs to patient interface module 55 and supervisory module 56. In onepreferred embodiment, patient interface module 55 and supervisory module56 remain external to the body of the patient. However either of thesedevices may be connected via percutaneous leads or be partially ortotally implanted without departing from the present invention.

[0070] Patient interface module 55 and supervisory module 56 facilitateadjustment of control parameters, monitoring of disease state,monitoring of response to therapy, monitoring of stimulating andrecording circuit 26, monitoring of impedance and other characteristicsof intracranial stimulating electrode array 37, monitoring ofphysiologic parameters, monitoring of vital signs, monitoring of anyother characteristic or function of components of the present invention,including but not limited to the stimulating and recording circuit 26,stimulating and recording unit 43, circuit enclosure 44, EMG electrodearray 50, EEG electrode array 51, accelerometer array 52, acoustictransducer array 53, peripheral nerve electrode array 54, andintracranial recording electrode array 38. Such monitoring andadjustment is accomplished through the use of any well knownbi-directional communication between control circuit 72 and supervisorymodule 56. In one preferred embodiment, a radio frequency link isemployed. In alternative embodiments, other communication technologies,including but not limited to optical, percutaneous, or electromagnetic,may be used.

[0071] In one preferred embodiment, patient interface module 55 andsupervisory module 56 are placed adjacent to the patients garmentsoverlying the implanted stimulating and recording unit 43. Whenneurological control system 999 is turned on in this position, acommunications handshaking protocol is executed. Communicationhandshaking routines are known to those or ordinary skill in the art,and they enable establishment of a communication rate and protocol andfacilitate mutual identification of devices. Patient interface module 55automatically downloads parameters from stimulating and recordingcircuit 26 and stores values of such parameters in a memory. When thetransfer of these parameter values is complete, patient interface module55 emits a audible signal such as a series of beeps, and the patientturns off patient interface module 55 and removes it from its positionoverlying the implanted stimulating and recording unit 43. Parametervalues may then be retrieved by the patient by a routine including butnot limited to a menu driven interface, and the values may betransmitted via telephone conversation or other communication method toa health care professional. Supervisory module 56 operates in the samemanner with one addition; a step is provided during which the healthcare professional may upload parameters to stimulating and recordingcircuit 26 to alter its function including by means of changingparameters including but not limited to control laws gains andthresholds, filter parameters, signal processing parameters, stimulationwaveform modes (including at least one of current regulated, voltageregulated, frequency regulated, or pulse width regulated), andstimulation waveform parameters.

[0072] Control laws, well known to those of ordinary skill in the fieldof control theory, are defined by a set of parameters specific to theparticular control law. Common parameters include preset gains,threshold levels, saturation amplitudes, sampling rates, and others.Adaptive controllers change in response to the behavior of the systembeing controlled; as such, in addition to preset parameters, adaptivecontrollers possess a set of varying parameters. These varyingparameters contain information indicative of the behavior of the systembeing controlled; downloading of these parameters provides one set ofmeasures of the disease state and its response to therapy.

[0073] Such monitoring includes observation of time history of diseasestate, stimulation parameters, response to therapy, and control lawparameters, including time-varying adaptive controller parameters. Suchadjustments includes modification of actual stimulation parameters andallowable ranges thereof, including but not limited to pulse width,pulse amplitude, interpulse interval, pulse frequency, number of pulsesper burst frequency. Adjustments can further include modification ofactual control law parameters and allowable ranges thereof, includingbut not limited to gains, thresholds and sampling rates of saidstimulation waveforms. Signal processor 71 contains signal processormodules for each of the sensory input modalities 247. Signal processingalgorithms for each of the said sensory input modalities 247 may beindependent. Additionally, signal processing algorithms the said sensoryinput modalities 247 may be coupled, such that the processing of one ofthe sensory input modalities 247 is dependent on another of the sensoryinput modalities 247. Adjustments may additionally include modificationof actual signal processor parameters and allowable ranges thereof,including but not limited to gains, filter cutoff frequencies, filtertime constants, thresholds, and sampling rates. In a preferredembodiment, the stimulation and control law parameters are stored in atleast one of random access memory and central processing unit registers(not shown).

[0074] It is anticipated that patient interface module 55 is to be usedby the patient, a family member or associate, or home health carepersonnel to monitor the functions and performance of neurologicalcontrol system 248. In such an embodiment, the use of the patientinterface module 55 is restricted to monitoring operations; adjustmentof stimulation and control parameters is not enabled. However,adjustment of all or a subset of stimulation and control parameters(described below) may be facilitated by patient interface module 55without departing from the present invention. Supervisory module 56, onthe other hand, is used by a physician or other health care personnel tomonitor function and performance of neurological control system 248 andto adjust stimulation and control parameters. Control parameterscontrolled by patient interface module 55 and supervisory module 56include allowable stimulation magnitude range, such as maximumcombination of stimulation voltage, current, pulse width, pulsefrequency, train frequency, pulse train count, pulse train duration.Control parameters may also include variables and constants used todefine control laws implemented in control circuit 72. Such controlparameters include, but are not limited to, control law gains 197-203,and other parameters for control laws, including but not limited toproportional controller 230, differential controller 204, integralcontroller 205, nonlinear controller 206, adaptive controller 207,sliding controller 208, model reference controller 209, and othercontrollers. In addition, amplitudes for other controller parameters,including but not limited to amplitudes for controller weights 210-216may be set by supervisory module 56. Additionally, the parametersspecifying the maximum amplitudes, or saturation values, may be set bysupervisory module 56. Control circuit 72 (FIG. 12) will be described indetail below.

[0075] The majority of the computation accomplished by stimulating andrecording circuit 26 is performed in signal conditioning unit 76, signalprocessor 71, and control circuit 72; the algorithms and behavior ofwhich are determined by corresponding sets of control parameters, ofwhich some may be set by the supervisory module 56 and a typically morerestricted set by patient interface module 55. In one embodiment,control parameters further includes signal conditioning parameters.Signal conditioning parameters may include, for example, amplifiergains, filter gains and bandwidths, threshold values, and otherparameters. In certain embodiments, control parameters additionallyinclude signal processing parameters, including envelope determinatorgains and time constants, filter passbands, filter gains, thresholdvalues, integrator gains, analyzer parameters, disease state estimatorparameters, artifact rejecter thresholds, envelope determinator timeconstants, rectifier parameters, spectral analyzer parameters and timerparameters.

[0076] In the illustrative embodiment described herein, controlparameters further include spike detector 188 (FIG. 9) parameters, spikecharacterizer 189 (FIG. 9) parameters, spike analyzer 190 (FIG. 9)parameters, spectral energy characterizer 192 (FIG. 9) parameters,spectral energy analyzer 193 (FIG. 9) parameters, aggregate diseasestate estimator 195 (FIG. 10) parameters.

[0077] In accordance with the present invention, tremor are quantifiedand monitored by any sensors over time as indicators of disease state.Such sensors include but are not limited to EMG electrode array 50, EEGelectrode array 51, accelerometer array 52, acoustic transducer array53, peripheral nerve electrode array 54, intracranial recordingelectrode array 38, and intracranial stimulating electrode array 37. Inone particular embodiment, the sensed tremor characteristics include,but are not limited to, magnitude, frequency, duration and frequency ofoccurrence of tremors. Changes in these and other parameters arecompared to current levels of, and changes in, treatment parameters.These changes are then used by aggregate disease state estimator 195 toestimate the response to therapy as functions of various electricalstimulation treatment parameters. Electrical stimulation treatmentparameters are adjusted by control circuit 72 in real-time to provideoptimal control of disease state.

[0078] Modulation parameters are optimized to achieve at least one ofminimization of disease state, minimization of symptoms of disease,minimization of stimulation magnitude, minimization of side effects, andany constant or time-varying weighted combination of these. Patientinterface module 55 and supervisory module 56 also preferably monitorthe function and operation of other components of neurological controlsystem 248, including stimulating and recording unit 26 and implantedcomponents 249.

[0079] Stimulating and recording unit 26 receives and processes signalsgenerated by implanted components 249 to provide conditioned signals78-84 to a signal processor 71. For each type of implanted components249 coupled to stimulating and recording unit 26, signal conditioningcircuit 76 preferably includes an associated amplifier and filter. Eachamplifier and associated filter is configured to receive and process thesignal generated by the associated one of the set of sensors 38, 51, 52,53, and 54.

[0080] In the illustrative embodiment, implanted components 249 includean electromyography (EMG) electrode array 50 which generate EMG signals.Preferably, EMG electrode array 50 comprises of all EMG electrodesimplemented in the particular embodiment of the present invention. Theseinclude, in the exemplary embodiment illustrated in FIG. 1, proximal EMGelectrode array 45, enclosure-mounted EMG electrode array 46 and distalEMG electrode array 47. Array 50 may also include, for example, EMGelectrodes implanted in the head or other location, and surface EMGelectrodes.

[0081] Implanted components 249 also include an electroencephalography(EEG) electrode array 51 which generate EEG signals and accelerometerarray 52 which generates acceleration signals. EEG electrodes 39, 40, 41illustrated in FIG. 1 are representative of EEG electrode array 51. EEGelectrodes 39-41 may be mounted directly to connecting cable 8 orconnected via intermediate cables. EEG electrode array 51 may includemore or fewer elements than EEG electrodes 39-41 depicted; and any ofnumerous standard and new electrode configurations, or montages, may beemployed without departing from the present invention.

[0082] Accelerometer array 52, which produces well-known accelerationsignals, preferably includes all accelerometers implemented in thepatient associated with the present invention. For example, in theembodiment illustrated in FIG. 1, accelerometer array 52 includeshead-mounted accelerometer 12, proximal accelerometer 28,enclosure-mounted accelerometer 36 and distal accelerometer 33.Accelerometer array 52 may include more or fewer accelerometers thanthese accelerometers, and accelerometers of any types and locations maybe employed without departing from the present invention.

[0083] Acoustic transducer array 53 includes all acoustic Sensorsutilized by the present invention. In the exemplary embodimentillustrated in FIG. 1, acoustic transducer array 53, includeshead-mounted acoustic sensor 11, proximal acoustic sensor 27,enclosure-mounted acoustic sensor 35 and distal acoustic sensor 19. Itshould be understood that acoustic transducer array 53 may include moreor fewer elements than said acoustic sensors listed above; and any ofnumerous acoustic sensor types and locations may be employed withoutdeparting from the present invention.

[0084] Peripheral nerve electrode array 54 generates peripheral neuralsignals, including but not limited to efferent and afferent axonalsignals. Preferably, peripheral nerve electrode array 54 includes allperipheral nerve electrodes implemented in present invention. Forexample, in the illustrative embodiment illustrated in FIG. 1,peripheral nerve electrode array 54 includes proximal peripheral nerveelectrode array 98 and distal peripheral nerve electrode array 99. Thesingle or plurality of individual peripheral nerve electrode arrayswhich comprise peripheral nerve electrode array 54 may be implanted inthe illustrated or other locations, as noted above.

[0085] Intracranial (IC) recording electrode array 38 generates centralneural signals, including but not limited to cortical, white matter, anddeep brain nuclear signals. Neural activity to be sensed includes but isnot limited to that found in the primary motor cortex, premotor cortex,supplementary motor cortex, somatosensory cortex, white matter tractsassociated with these cortical areas, the globus pallidus internalsegment, the globus pallidus external segment, the caudate, the putamen,and other cortical and subcortical areas. As one of ordinary skill inthe relevant art will find apparent, the present invention may includeadditional or different types of sensors that sense neural responses forthe type and particular patient. Such sensors generate sensed signalsthat may be conditioned to generate conditioned signals as describedbelow. One example of the placement of these electrodes is describedabove with reference to the embodiment illustrated in FIG. 1. Manyothers are contemplated by the present invention.

[0086] As noted, for each of the different types of sensors included inimplanted components 249, signal conditioning circuit 76 includes anassociated amplifier and filter in the illustrative embodiment.Accordingly, signal conditioning circuit 76 includes an EMG amplifier 59and filter 66, each constructed and arranged to amplify and filter,respectively, the EMG signals received from EMG electrode array 50.Similarly, signal conditioning circuit 76 also includes an EEG amplifier60 and filter 67, accelerometer (ACC) amplifier 61 and filter 68,acoustic (ACO) amplifier 62 and filter 69, peripheral nerve electrode(PNE) amplifier 63 and filter 70 and intracranial (IC) recordingelectrode (ICRE) amplifier 58 and filter 65.

[0087] Simplifiers 57-63 may be single or multi-channel amplifiersdepending upon the number of electrodes with which it interfaces. In onepreferred embodiment, amplifiers 57-63 are physically located in thesame enclosure as filters 64-70; that is, in a single signalconditioning circuit 76. Preferably, signal conditioning circuit 76 isphysically contained within stimulating and recording unit 102. However,amplifiers 57-63 may be located separately from stimulating recordingunit 102. For example, amplifiers 57-63 may be affixed to or situatedproximate to their associated electrode arrays 38, 50-54. Thisarrangement facilitates the preamplification of the associated signalsgenerated by the associated electrode arrays 38, 50-54, increasing thesignal-to-noise ratio of the signals. Amplifiers 57-63 may be any knownvoltage amplifier now or later developed suitable for amplifying theparticular signals generated by their associated electrodes.

[0088] As noted, the amplified signals are passed to their associatedfilters 64-70 as shown in FIG. 2. As with amplifiers 57-59, filters64-70 may be physically separate from or incorporated into signalconditioning circuit 76 and stimulating and recording unit 26. In onepreferred embodiment, filters 64-70 are low pass filters having acut-off frequency of, for example, 3,000 Hz. In alternative embodiments,filters 64-70 may include a notch filter to remove, for example, 60 Hznoise, or other types of filters appropriate for the type of signalsgenerated by the associated sensors 38, 51, 52, 53, and 54. Selection ofthe appropriate frequencies for the cut-off and notch filter frequenciesis considered to be well known in the relevant art and within the scopeof the present invention. Filters 66-70, 65 and 64 generate conditionedsensed signals 84, 83 and 78-82, respectively.

[0089] Signal processor 71 processes the conditioned sensed neuralresponse signals 78-84 generated by signal conditioning circuit 76 inaccordance with the present invention to determine neural system states.Signal processor 71 generally performs well known filtering operationsin the time and frequency domains. In one preferred embodiment, theneural system states include one or more physiologic or disease states.Signal processor 71, which can be implemented in a fast microprocessor,a DSP (digital signal processor) chip, or as analog circuitry, forexample, is described in detail below.

[0090] Control circuit 72, responsive to the signal processor 71,patient interface module 55 and supervisory module 56, adjusts themagnitude of a neural modulation signal in response to the sensed neuralresponse. Signal processor 71 extracts relevant information from thesensed conditione signals, and control circuit 72 uses this extractedinformation in the calculation of an output neuromodulation signal (NMS)998. Neuromodulation signal 998 subsequently travels along stimulatoroutput path 111 to IC stimulating electrode array 37. In one embodiment,control circuit 72 is a state machine, utilizing current and past systembehavior in the calculation of a control signal. In an alternativeembodiment, control circuit 72 includes an embedded microprocessor toprocess nonlinear control laws. Alternative embodiments of the controlcircuit 72 appropriate for the particular application may be also beused.

[0091] Control circuit 72 receives control law selection information,control law parameter information, stimulation waveform parameter rangeinformation, stimulation modulation mode, output stage regulation mode,and medication dose and timing information from patient interface module55 and supervisory module 56. The waveform parameter or parameters whichare modulated by control law output signal U 997 are determined by thestimulation modulation mode; these parameters include but are notlimited to pulse amplitude, pulse width, pulse frequency, pulses perburst, and burst frequency. Selection between regulation of pulsevoltage or pulse current as the regulated pulse amplitude is determinedby the output stage regulation mode.

[0092] Control circuit 72 provides stimulation waveform parameterhistory information, disease state history information, control lawstate variable history information, control law error historyinformation, control law input variable history information, control lawoutput variable history information, stimulating electrode impedancehistory information, sensory input history information, battery voltagehistory information, and power consumption history information topatient interface module 55 and supervisory module 56.

[0093] Provision of stimulating electrode impedance history informationallows monitoring of stimulating electrode performance andfunctionality. If an electrode is determined to be fractured, shorted,or encapsulated by fibrotic tissue, any of various control lawparameters, output stage parameters, and waveform range parameters maybe adjusted to allow compensation for these changes. Additionally, theNeuromodulation Signal (NMS) 998 may be delivered to different sets ofelectrodes to insure that it reaches neural tissue 250. Sensory inputhistory information allows evaluation of validity of any given sensoryinput. This is useful in determining the functionality of a given sensorand serves as an indicator for sensor replacement or adjustment of thesignal processing parameters or algorithm or the control law parametersor algorithm to continue to generate reliable disease state estimatesignals X and control law outputs U despite the loss of any particularindividual or set of sensory signals.

[0094] Signal processor 71 receives amplifier gain setting information,filter parameter information, weighting information, and disease stateestimator parameter and algorithm information from patient interfacemodule 55 and supervisory module 56. The function and operation ofpatient interface module 55 and supervisory module 56 are describedabove. As noted, patient interface module 55 may be used by the patientor home health care personnel to monitor disease state, stimulationparameters, and response to therapy. Limited adjustment of stimulationparameters and ranges is facilitated. Patient interface module 55 may beused by the patient or home health care personnel to provide informationto the physician, avoiding the need for an office visit for theobtainment of said information.

[0095] Patient information module 55 queries signal processor 71 forpresent and time histories of monitored values. Time histories ofselected variables in signal processor 71 and control circuit 72 arestored in memory module 240 for subsequent retrieval by patientinterface module 55 and supervisory module 56. Selected variablesinclude but are not limited to disease state, tremor frequency, tremormagnitude, EMG magnitude, EMG frequency spectra (EMG magnitude withinfrequency ranges), and acceleration of limb, head, mandible, or torso.Selected variables may also include disease state, frequency spectra oflimb, torso, and head movements, as determined by EMG and accelerometersignals.

[0096] Stimulating and recording unit 26 also includes an output stagecircuit 77. Output stage circuit 77 takes for an input the control lawoutput signal U, which may be comprised of a single or multiplicity ofchannels or signals, from control circuit 72. This control law outputsignal U 997 modulates the magnitude of the sequence of waveformscomprising the desired output neuromodulation signal (NMS_(D)) which isproduced by output stage circuit 77 and delivered via intracranialstimulating electrode array 37 to neural tissue 250.

[0097] Output stage circuit 77 generates a neuromodulation signal(NMS_(D)) 998 with a magnitude specified by control law output signal U997 received from control circuit 72. In one preferred embodiment, thewaveform parameter of the desired output neuromodulation signal(NMS_(D)) which is modulated by control law output signal U is thestimulation current magnitude. The capability to specifically modulatethe stimulation current confers efficacy resistance to perturbations orchanges in electrode impedance. Presently implanted systems suffer froma decline in efficacy which results from an increase in electrodeimpedance which accompanies the normal tissue response to a foreignbody, that is fibrotic encapsulation of the electrode. In this designtaught in the present invention, a the magnitude of the currentdelivered to the neural tissue 250 will not vary as the electrodebecomes encapsulated with fibrotic tissue or its impedance otherwisechanges over time. A further advantage conferred by current modulationis the ability to monitor electrode impedance. If a current-modulatedwaveform, preferably a sinusoid, is delivered to the electrodes, and theresultant voltage potential waveform is concurrently monitored, therelative magnitudes and phase shifts of these waveforms may be computed.From these magnitudes and phases, the complex impedance and hence theresistive and capacitive components of the electrode impedance may becalculated.

[0098] In an alternative embodiment, the waveform parameter of thedesired output neuromodulation signal (NMS_(D)) which is modulated bycontrol law output signal U 997 is the stimulation voltage magnitude.This design would not enjoy the independence of the stimulation currentand efficacy from impedance variation enjoyed by the embodimentdescribed above. If fibrosis was uneven around the surface of theelectrode, this embodiment would avoid potentially undesirably largecurrent densities along narrow tracts of remaining low resistanceunfibrosed regions of neural tissue 250.

[0099] Alternatively, regulation of stimulus pulse width may be desired.In certain circuit implementations, the available resolution or bits forspecifying the magnitude of pulse width may be greater than that forspecifying the pulse voltage or current. In such a case, if finercontrol of the magnitude of Neuromodulation signal (NMS) 998 is desiredthan is provided by the control of pulse current or pulse voltage, thenit may be desirable to modulate the pulse width. Furthermore, thespatial neuron recruitment characteristics of a pulse width modulatedneuromodulation signal (NMS) 998 may provide a more linear, predictable,or controllable response than that obtained with current or voltagemodulation. Selection between regulation of pulse voltage, pulsecurrent, or pulse width as the regulated pulse amplitude parameter isdetermined by the output stage regulation mode, which may be set usingsupervisory module 56. In alternative embodiments, the modulation ofpulse frequency and the modulation of the number of pulses per burst areregulated. As one of ordinary skill in the relevant art would findapparent. Other such characteristics may be regulated in addition to orinstead of the ones noted above.

[0100] Output stage circuit 77 includes a pulse generator 73, an outputamplifier 74 and a multiplexor 75. Pulse generator 73 generates one ormore stimulus waveforms, each of which is characterized by severalparameters, including but not limited to pulse amplitude, pulse width,pulse frequency, number of pulses per burst, and burst frequency. Asnoted above, pulse amplitude may comprise pulse voltage or pulsecurrent. Preferably, each of these parameters may be independentlyvaried, as specified by control law output signal U 997 generated bycontrol circuit 72. As noted, the stimulus waveforms comprising theneuromodulation signal (NMS) generated by output stage circuit 77 areapplied to patient through intracranial (IC) stimulating electrode array37. Pulse generator 73 generates a single waveform when single channelstimulation is to be used, and a plurality of waveforms when multiplechannel stimulation is to be used. It may generate monophasic orbiphasic waveforms.

[0101] In one preferred embodiment, charge balanced biphasic waveformsare produced. Those skilled in the art are aware that the net chargecontained in a given pulse is given by the time integral of the stimuluscurrent over the duration of the pulse. In a biphasic configuration, apair of pulses of opposite polarity is generated, and the pulse currentamplitude and pulse width are chosen such that the charge amplitude isequal in magnitude and opposite in polarity. In some cases, it isdesirable for the pulses comprising the biphasic pulse pair to havedifferent amplitudes; in this case, the pulse widths are chosen toinsure equal and opposite charges so the pulse par introduces zero netcharge to the neural tissue 250. The capability to deliver pulse pairswith balanced charges is yet a further advantage conferred by thecurrent regulation mode described above.

[0102] Even though the waveform parameters of the pulse pairs arecalculated to deliver a zero net charge, in practice, noise andprecision limitations in computation and resolution limitations andnonlinearities in the digital to analog conversion and amplificationstages may result in slight imbalances in the pulse pair charges. Overtime, this can result in the delivery of a substantial accumulated netcharge to the neural tissue. To eliminate this potential for net chargedelivery to neural tissue, a direct current (DC) blocking capacitor isemployed. This is a technique that is well known to those or ordinaryskill in the art. In one preferred embodiment, a DC blocking capacitoris included within multiplexor 75 in series with stimulator output path111.

[0103] Typically, multichannel stimulation is used in the case ofbilateral stimulation. Since the disease progression is typicallyasymmetrical, and the normal motor control systems governing movement onthe left and right side of the body are also highly independent of eachother, the delivery of treatment to the left and right sides of the bodyshould be controlled separately. This represents one need for a multiplechannel neuromodulation signal (NMS) 998. Multichannel stimulation isalso expected to be beneficial in treating patients with variableinvolvement of different limbs. For example, the magnitudeneuromodulation of a portion of the globus pallidus required to achieveoptimal controls of arm tremor may be different from the optimal levelof neuromodulation of separate portion of the globus pallidus to achieveoptimal control of leg tremor. In this case, separate electrodes orelectrode pairs are required to deliver optimal levels ofneuromodulation to control tremor in these two regions of the body.Correspondingly, these separate electrodes or electrode pairs will bedriven by separate neuromodulation signal (NMS) channels, necessitatinga multichannel system.

[0104] A further need for multichannel neuromodulation signal (NMS) isthe control of multiple symptoms of the movement disorder and the sideeffects arising from pharmacologic treatment. Optimal control of tremor,dyskinesias, and rigidity are not achieved by modulation of the samesite at the same intensity. For this reason, multiple and separatelycontrolled channels of neuromodulation are required to simultaneouslyachieve optimal control of these multiple symptoms and side effects.Each of these symptoms and side effects may be considered to compriseone or more element in a multivariable disease state. A multivariablecontrol system will be required to optimally drive each of these diseasestate elements to its desired value, ideally toward a target minimumlevel and thus achieve optimal control of this multiplicity of diseasestates. This multivariable control system may be implemented as multipleindependent control laws each with separate though potentiallyoverlapping sensory inputs or as a multivariable control law matrix.

[0105] Stimulation via each of the multiple channels comprising theneuromodulation signal (NMS) 998 is characterized by separate thoughpossibly overlapping sets of one or more of the following parameters:stimulation voltage, stimulation current stimulation frequency of pulseswithin the same burst, frequency of bursts, pulse width, pulses perburst, duration of burst, and interpulse interval. The stimuluswaveforms are amplified by output amplifier 74 to generate an amplifiedstimulus waveform. Specifically, pulse generator 73 transfersinformation to output amplifier 74 which includes information thatuniquely specifies the desired stimulation waveform. In a preferredembodiment, the information is in the form of an analog signal whichrepresents a sealed version of the voltage or current waveform to bedelivered to the tissue. It should be understood that other forms of thesignal generated by pulse generator 73 may be used, includingcombinations of at least one of analog and digital representations.Output amplifier 74 performs amplification and regulation of thereceived stimulus waveform generated by the pulse generator 73. This maybe regulation of electrical current to achieve desired voltage orregulation of electrical voltage to achieve desired current, dependingon whether a voltage or current waveform is to be delivered to thenervous system component.

[0106] As one skilled in the relevant art would find apparent, voltageregulation is simpler to implement, and is a technique which is commonlyused by many conventional stimulators. Current regulation, on the otherhand, is more complex but allows for more precise control of the appliedstimulation. Current regulation insures that a specified amount ofcurrent is delivered, regardless of the impedance of the electrode.Current regulation is advantageous in that it allows for precise controlof stimulation level despite changes in electrode impedance whichinvariably occur over time. Since electrode impedances often change,typically increasing as they become encapsulated by fibrosis, currentregulation is preferred to avoid the decrease in current which wouldoccur if voltage regulation were to be used in such circumstances.

[0107] The amplified stimulus waveform generated by output amplifier 74is conducted along stimulator amplifier output path 112 to multiplexor75. Multiplexor 75 allows for delivery of a stimulating electrode outputsignal (SEOS) to the intracranial stimulating electrode array 37,multiplexed with sensing of a stimulating electrode input signal (SEIS).Specifically, multiplexor 75 serves to alternately connect intracranialstimulating electrode (ICSE) array 37 to output amplifier 74 andintracranial stimulating electrode amplifier 57. Connection ofintracranial stimulating electrode (ICSE) array 37 to output amplifier74 facilitates delivery of neural modulation signal to neural tissue,while connection of intracranial stimulating electrode (ICSE) array 37to intracranial stimulating electrode amplifier 57 facilitatesmonitoring of neural activity in the region being stimulated.

[0108] Multiplexor 75 allows delivery of neural modulation signals toneural tissue concurrent with monitoring of activity of same neuraltissue; this facilitates real-time monitoring of disease state andresponse to treatment. Stimulating electrode output signal (SEOS) fromoutput amplifier 74 is conducted along stimulator amplifier output path112 to multiplexor 75. Multiplexor 75 conducts output from outputamplifier 74 to stimulator output path 111 which conducts thestimulating electrode output signal to intracranial stimulatingelectrode array 37. To facilitate periodic sampling of neural activityin tissue being stimulated, multiplexor 75 alternatively conducts signalarising from stimulated tissue via intracranial stimulating electrodearray (ICSE) 37 and stimulator output path 111 to multiplexed stimulatorrecording input path 113 and intracranial stimulating electrodeamplifier 57.

[0109] Multiplexor 75 selectively conducts the signal on multiplexedstimulator recording input path 113 to amplifier 57. Multiplexor 75 mayalternate conduction between path 111 and path 112 or path 113 usingtemporal multiplexing, frequency multiplexing or other techniques toallow concurrent access to the intracranial stimulating electrode (ICSE)array 37 for modulation of tissue activity and monitoring of tissueactivity. Temporal multiplexing is a well known technique and frequencymultiplexing of stimulation and recording signals in known to thoseskilled in the art. In this embodiment, temporal multiplexing isaccomplished by alternately connecting stimulator output path 111 tostimulator amplifier output path 112 and multiplexed stimulatorrecording input path 113. In one embodiment, frequency multiplexing isaccomplished by passing a band-limited portion of stimulating electrodeoutput signal SEOS via the stimulator output path 111 to intracranialstimulating electrode array 37 while simultaneously monitoring activityon intracranial stimulating electrode array 37 within a separatefrequency band, thereby generating a stimulating electrode input signalSEIS. Thus, stimulating electrode input signal SEIS is conducted fromthe intracranial stimulating electrode array 37 to stimulator outputpath 111 to multiplexor 75 and via multiplexed stimulator recordinginput path 113 to intracranial stimulating electrode array amplifier 57.

[0110] Multiplexor 75 facilitates conduction between stimulatoramplifier output path 112 and multiplexed stimulator recording inputpath 113 to allow automated calibration. In this mode, a calibrationsignal of known amplitude is generated by pulse generator 73 andamplified by output amplifier 74 which, for calibration purposes,delivers a voltage regulated signal via stimulator amplifier output path112 to multiplexor 75. Multiplexor 75 conducts amplified calibrationsignal to multiplexed stimulator recording input path 113 which conductssignal to intracranial stimulating electrode amplifier 57.

[0111] Although not included in the illustrative embodiment, multiplexedor intermittent connection of stimulator amplifier output path 112 tothe inputs of at least on of the other amplifiers, including EMGamplifier 59, EEG amplifier 60, accelerometer amplifier 61, acousticamplifier 62, peripheral nerve electrode amplifier 63, and intracranialrecording electrode amplifier 58, may be implemented without departingfrom the present invention. The same multiplexed connections may be usedto calibrate the pulse generator 73 and output amplifier 74.

[0112] Referring to FIG. 15, an analog switch may be used to connect oneor an opposing polarity pair of Zener diodes across the noninverting andinverting inputs of intracranial recording electrode amplifier 58. Inthis configuration, the Zener diodes would limit the maximal amplitudeof the calibration signal in one or both polarities to known values,allowing for accurate calibration of intracranial recording electrodeamplifier 58. The analog switch may then be deactivated, removing thecathode of the single or pair of Zener diodes from the input ofintracranial recording electrode amplifier 58 to allow measurement ofstimulating electrode output signal (SEOS) for calibration of pulsegenerator 73 and output amplifier 74. This is described in greaterdetail below.

[0113] Multiplexor 75 also facilitates conduction between stimulatoramplifier output path 112, multiplexed stimulator recording input path113, and stimulator output path 111 to allow measurement of impedancesof components of intracranial stimulating electrode array 37. In thiselectrode impedance measurement mode, a three way connection betweenstimulator amplifier output path 112, multiplexed stimulator recordinginput path 113, and stimulator output path 111 is created. When outputamplifier 74 is operated in current regulated mode, it delivers an SEOSof known current via stimulator output path 111 to intracranialstimulating electrode array 37. The voltages generated across theelements of intracranial stimulating electrode array 37 generally arethe products of the electrode impedances and the known stimulatingcurrents. These voltages are sensed as the stimulating electrode inputsignal SEIS by the intracranial stimulating electrical amplifier 57.

[0114] Reference module 116 contains memory registers in which controllaw reference values are stored. Such reference values include but arenot limited to target disease state levels, target symptom levels,including target tremor level, and threshold levels. Threshold levelsinclude but are not limited to disease and symptom levels, includingtremor threshold levels. Neural modulation amplitude may be increasedwhen at least one of disease state and symptom level exceed thecorresponding threshold. Similarly neural modulation amplitude may bedecreased or reduced to zero when either the disease state or symptomlevel falls below the corresponding threshold.

[0115] Reference module 116 is connected to patient interface module 55,facilitating both monitoring and adjustment of reference values bypatient. Reference module 116 is also connected to supervisory module56, facilitating both monitoring and adjustment of reference values byphysician or other health care provider. Supervisory module 56 may beused by the neurologist, neurosurgeon, or other health careprofessional, to adjust disease state reference R values for the one ormore control laws implemented in control circuit 72. The disease statereference R values specify the target level at which the correspondingdisease states are to be maintained, as quantified by the disease stateestimate X values, providing reference values for control lawsimplemented in control law circuit block 231 (FIG. 11; discussed below)and contained within control circuit 72. Reference module 116 may alsoreceive input from control circuit 72, facilitating the dynamicadjustment of reference disease state “r” (discussed below). Referencemodule 116 may additionally receive input from disease state estimatormodule array (DSEMA) 229 (FIG. 11; discussed below) and aggregatedisease state estimator 195 (FIG. 11; discussed below) and components ofsignal processor 71, for use in dynamically determining referencedisease state “r”.

[0116]FIG. 10 is a schematic diagram of signal processor 71. In thisillustrative embodiment, signal processor 71 includes a disease stateestimator module array 229 that includes one or more signal processormodules that generate a quantitative estimate of at least one diseasestate or parameter thereof based upon its respective input. For example,magnitude of tremor in the 3 to 5 Hz range represents one possiblerepresentation of a disease state. This could be an absolute ornormalized quantification of limb acceleration in meters per secondsquared. This component of the disease state would be calculated almostexclusively from sensory feedback from accelerometer array 52. Anotherpossible disease state is the frequency of occurrence of episodes oftremor activity per hour. This element of the disease state may beestimated from any of several of the sensory feedback signals. In thiscase, the most accurate representation of this disease state element isobtained by applying a filter such as a Kalman filter to calculate thisparameter based upon a weighted combination of the sensory feedbacksignals. Such weighting coefficients are calculated from quantifiedmeasures of the accuracy of and noise present upon each sensory feedbackchannel.

[0117] In the illustrative embodiment, disease state estimator modulearray 229 includes an EMG signal processor 233, EEG signal processor234, accelerometer signal processor 235, acoustic signal processor 236,peripheral nerve electrode (PNE) signal processor 237, intracranialrecording electrode (ICRE) signal processor 238, and intracranialstimulating electrode (ICSE) signal processor 239. It should beunderstood that other signal processors may also be included in thearray 229. Inputs to these modules include conditioned EMG signal path78, conditioned EEG signal path 79, conditioned accelerometer signalpath 80, conditioned acoustic signal path 81, conditioned peripheralnerve electrode (PNE) signal path 82, conditioned intracranial recordingelectrode (ICRE) signal path 83, and conditioned intracranialstimulating electrode (ICSE) signal path 84, respectively. Communicationbetween these modules is facilitated. The output(s) of each of themodules is connected to an aggregate disease state estimator 195.Aggregate disease state estimator 195 generates a single or plurality ofdisease state estimates “X” indicative of state of disease and responseto treatment.

[0118] In the preferred embodiment, the acceleration of at least one ofthe affected limb and the head, each of which is sensed as a sensoryfeedback channel by an element of the accelerometer array 52, serves asrespective elements in the disease state estimate X. These elements ofdisease state estimate X are inputs to respective control lawsimplemented in control circuit 72, of input to the control law. Acontrol law governing the function of a proportional controller usingacceleration as its single sensory feedback channel is given by equation(1):

u ₁=0.3166 (V*s ² /m)*ACC  (1)

[0119] and if

u ₂=0.6333 (V*s ² /m)*ACC  (2)

[0120] where u₁ and u₁ are the stimulation voltage given in volts; andACC is the limb, mandible, or head acceleration given in meters persecond squared (m/s²).

[0121] In equation (1), the stimulation site is the ventroposterolateralpallidum, the output stage mode is voltage regulated, the waveform is acontinuous train of square waves, the amplitude u₁ is given in volts(typically approximately 1 volt), and the remaining stimulationparameters include a pulse width of 210 microseconds, and a stimulationfrequency of 130 Hz. In equation (2), the stimulation site is theventral intermediate thalamic nucleus (Vim), the output stage mode isvoltage regulated, the waveform is an intermittent train of square waveswith an on time of 5 minutes and an off time of 45 seconds, theamplitude u₂ is given in volts (typically approximately 3 volts), andthe remaining stimulation parameters include a pulse width of 60microseconds, and a stimulation frequency of 130 Hz.

[0122] In one preferred embodiment, the ACC signal represents theaverage acceleration over a finite time window, typically 15 to 60seconds. This effective lowpass filtering provides a stable sensoryfeedback signal for which a proportional control law is appropriate. Ifstability and performance requirements dictate, as is familiar to thosepracticed in the art of feedback control, other components, including anintegrator and a differentiator may be added to the control law toproduce a proportional-integral-differential (PID) controller, asneeded.

[0123] One preferred embodiment also includes electromyographic (EMG)signals as sensory feedback in the calculation of at least one elementof the disease state estimate X which is an input to the control law. Asdiscussed in the section describing EMG signal processor 233, the EMGsignals are rectified by full wave rectifier 123, passed throughenvelope determiner 124, passed through several bandpass filters 125,127, 129, 131, 133 and associated threshold discriminators 126, 128,130, 132, 134 and then passed in parallel to each of integrator 135 andcounter 136. Integrator 135 generates an output which is a weightedfunction of it inputs and represents the average magnitude of tremoractivity over a given time window −w/2 to +w/2. A simplifiedrepresentation of this is given by equation (3): $\begin{matrix}{u_{3} = {\int_{{- w}/2}^{w/2}{X_{EMG} \cdot {t}}}} & (3)\end{matrix}$

[0124] over a given time window −w/2 to +w/2. A simplifiedrepresentation of this is given by the equation:

[0125] As is familiar to those skilled in the art of control theory, anintegral controller is marginally stable. To confer stability to thiscontrol law, the equivalent of a finite leak of the output magnitude u₄to zero is added to maintain stability. A more general form of thisequation is given by equation (4): $\begin{matrix}{{{{\cdot C_{1}}\frac{\partial u_{4}}{t}} + {C_{2} \cdot u_{4}}} = {{B_{1} \cdot \frac{\partial{\overset{\_}{X}}_{EMG}}{t}} + {B_{2} \cdot {\overset{\_}{X}}_{EMG}}}} & (4)\end{matrix}$

[0126] Shown as a system function, the control law output U is given asthe product of a transfer function H(s) and the disease estimate X, theinput to the control law:

u(s)(C ₁ ·s+C ₂)=X _(EMG)(s)(B ₁ ·s+B ₂)  (5)

[0127] $\begin{matrix}{\frac{u(s)}{X_{EMG}(s)} - \frac{\left. {{B_{1} \cdot s} + B_{2}} \right)}{\left( {{C_{1} \cdot s} + C_{2}} \right)}} & (6) \\{{H(s)} = {\frac{u(s)}{X_{EMG}(s)} - \frac{\left( {{B_{1} \cdot s} + B_{2}} \right)}{\left( {{C_{1} \cdot s} + C_{2}} \right)}}} & (7)\end{matrix}$

[0128] One such control law with an appropriate time response is givenby: $\begin{matrix}{{H(s)} = {\frac{u(s)}{X_{EMG}(s)} = \frac{G_{VIEMG}\left( {{0.1 \cdot s} + 1} \right)}{\left( {{2 \cdot s} + 1} \right)}}} & (8)\end{matrix}$

[0129] where G_(V/EMG) is the gain in neuromodulation signal (NMS)(volts per volt of EMG signal).

[0130] For intramuscular EMG electrodes, signal amplitudes are on theorder of 100 microvolts. For neuromodulation signal (NMS) parameters of2 volts amplitude, 60 microseconds pulse width, 130 Hz stimulationfrequency, the appropriate overall gain G′_(V/EMG) is 20,000volts_(NMS)/volts_(EMG). Since the preamplifier stage performsamplification, 1000, in the preferred embodiment, the actual value forG_(V/EMG) as implemented in the control law is 20volts_(NMS)/volts_(PREAMPL EMG).

[0131] Disease state estimator 195 determines estimates of disease stateincluding but not limited to long-term, or baseline, components,circadian components, postprandial components, medication inducedalleviation of components, medication induced components, and futurepredicted behavior of said components. Output of disease state estimator195 includes output of observer 228, depicted in FIG. 11, which makesuse of an adaptive model of disease behavior to estimate disease stateswhich are not directly detectable from sensors. Such sensors, provideinput to the adaptive model to correct state estimates and modelparameters. Each of the signal processor modules in disease stateestimator module array 229 are described below.

[0132]FIG. 3 is a block diagram of intracranial recording electrode(ICRE) signal processor 238 and intracranial stimulating electrode(ICSE) signal processor 239, each of which are included within signalprocessor 71 in the illustrative embodiment illustrated in FIGS. 2 and10. ICRE signal processor module 238 and ICSE signal processor module239 process signals from one or more intracranial electrodes, includingbut not limited to those comprising intracranial recording electrodearray 38 and intracranial stimulating electrode array 37. As noted,intracranial stimulating electrode array 37 is comprised of one or moreintracranial stimulating electrodes while intracranial recordingelectrode array 38 is comprised of one or more intracranial recordingelectrodes.

[0133] Input to ICRE signal processor 238 is conditioned intracranialrecording electrode (ICRE) signal path 83 noted above. This input isconnected to a spike detector 85 which identifies action potentials.Spike detection techniques are well known to those skilled in the artand generally employ low and high amplitude thresholds. Waveforms havingamplitudes greater than the low threshold and lower than the highthreshold are determined to be action potentials. These thresholds maybe predetermined or adjusted manually using supervisory module 56 or maybe adapted in real-time by an algorithm which sweeps the thresholdthrough a range of values to search for values at which action potentialspikes are consistently recorded. The low amplitude threshold is setabove the amplitude of background noise and that of nearby cells not ofinterest, and the high amplitude threshold is set above the amplitude ofthe desired action potentials to allow their passage while eliminatinghigher amplitude noise spikes, such as artifacts arising from electricalstimulation currents. Bandpass, notch, and other filtering techniquesmay also be used to improve signal to noise ratio and the sensitivityand specificity of spike detectors. Individual neuron action potentialsare usually recorded using fine point high-impedance electrodes, withimpedances typically ranging from 1 to 5 megohms. Alternatively, largerlower-impedance electrodes may be used for recording, in which case thesignals obtained typically represent aggregate activity of populationsof neurons rather than action potentials from individual neurons.

[0134] Spike detector 85 passes the waveform(s) to a spike characterizer86. Spike characterizer 86 determines firing patterns of individualneurons. The patterns include, for example, tonic activity, episodicactivity, and burst firing. Spike characterizer 86 calculates parametersthat characterize the behavior of the individual and groups of neurons,the activity of which is sensed by intracranial recording electrodearray 38. In one embodiment, the characterization includesparameterization of recorded action potentials, also referred to asspikes, bursts of spikes, and overall neural activity patterns. Thisparameterization includes, but is not limited to, calculation offrequencies of spikes, frequencies of bursts of spikes, inter-spikeintervals, spike amplitudes, peak-to-valley times, valley-to-peak times,spectral composition, positive phase amplitudes, negative phaseamplitudes, and positive-negative phase differential amplitudes. Theseparameters are depicted in FIG. 14 and are discussed below. Based onthese parameterization, spike characterizer 86 discriminates individualspikes and bursts originating from different neurons. Thisdiscrimination facilitates serial monitoring of activity of individualand groups of neurons and the assessment and quantification of activitychange, reflective of change in disease state and of response totherapy.

[0135] A spike analyzer 87 receives as input the parameters from spikecharacterizer 86. Spike analyzer 87 extracts higher level information,including but not limited to average spike frequencies, averageinterspike intervals, average amplitudes, standard deviations thereof,trends, and temporal patterning. By comparing current spike frequencyrates to historical spike frequency data, spike analyzer 87 additionallycalculates the rates of change of spike parameters. Prior trends andcurrent rates of change may then be used to predict future behaviors.Rates of change of the parameters include but are not limited toautocorrelation and digital filtering.

[0136] Spike analyzer 87 may receive additional input fromaccelerometers, including but not limited to at least one of headmounted accelerometer 12, proximal accelerometer 28, enclosure mountedaccelerometer 36, and distal accelerometer 33. Spike analyzer 87 mayreceive indirect input from accelerometers, such as from conditioned orprocessed signals arising therefrom. This may include, for example, thesignal transmitted by conditioned accelerometer signal path 80.

[0137] Spike analyzer 87 may also receive additional input from EMGarrays 50, such as a proximal EMG electrode array 45, enclosure-mountedEMG electrode array 46, or distal EMG electrode array 47. Spike analyzer87 may receive indirect input from such EMG electrode arrays 50, such asfrom conditioned or processed signals arising therefrom, including butnot limited to the signal transmitted by conditioned EMG signal path 78.

[0138] These additional inputs from accelerometers and EMG arraysfacilitates the characterization of neuronal firing patterns relative toactivity of muscle groups and movement of joints, including but notlimited to characterization of neuronal spike amplitudes and tuning offiring to movement, including but not limited to movement velocity anddirection. The characterization may be used to assess functioning of thesensorimotor system, including but not limited to motor response time,and to measure the disease state and response to therapy.

[0139] Intracranial recording electrode (ICRE) single unit-based (SU)disease state estimator 88 receives input from spike characterizer 86and/or spike analyzer 87. Spike analyzer 87 provides higher levelinformation, including but not limited to average spike frequencies,average interspike intervals, average amplitudes, standard deviationsthereof, trends, and temporal patterning to disease state estimator 88 .These inputs are representative of the current neuronal activity in thetissue from which the intracranial recording electrodes (ICRE) arerecording. ICRE SU disease state estimator 88 may also receive inputrepresentative of one or more signals, including desired neuronalactivity, from control circuit 72. The ICRE SU disease state estimateX_(ICRE) _(—) _(SU) calculated by ICRE SU disease state estimator 88,may be comprised of a single or a plurality of signals, consistent witha representation of the disease state by a single or a multitude ofstate variables, respectively. The ICRE MU disease state estimateX_(ICRI MU) calculated by ICRE MU disease state estimator 88, may becomprised of a single or a plurality of signals, each representative ofmultiunit neurophysiological signals, i.e. reflective of concurrentactivity of numerous neurons. Both ICRE SU disease state estimateX_(ICRE SU) and ICRE MU disease state estimate X_(ICRE) _(—) _(MU) areoutput to aggregate disease state estimator 195.

[0140] Referring to FIG. 3, conditioned intracranial recording electrode(ICRE) signal path 83 additionally connects to filter 101. Filter 101 ispreferably of the bandpass type filter. In one embodiment, the bandpassfilter 101 has a passband of 0.1 to 100 Hz, although other ranges may beused. Output of filter 101 connects to spectral energy characterizer102, which may be implemented in any of several hardware or softwareforms. For example, in one embodiment, the spectral energy characterizer102 is implemented using real-time fast Fourier transform (FFT)techniques. Alternatively, other digital or analog techniques may alsobe used.

[0141] It should be understood that inputs and outputs from spikedetector 85, spike characterizer 86, spike analyzer 87, disease stateestimator 88, filter 101, spectral energy characterizer 102, spectralenergy analyzer 103, and disease state estimator 104 may be comprised ofindividual signals or a plurality of signals. Further, spike detector85, spike characterizer 86, spike analyzer 87, disease state estimator88, filter 101, spectral energy characterizer 102, spectral energyanalyzer 103, and disease state estimator 104 may each have differentparameters and signal processing characteristics for each of themultiple signals processed. Because baseline neuronal firing ratesdiffer among various anatomical and functional regions of the brain, andtheir involvement in disease states and susceptibility to change infiring patterns varies, the respective signal processing circuitry andlogic will vary correspondingly. For example, baseline firing ratesamong neurons in the globus pallidus externus are approximately 43 Hzand those in the globus pallidus internus are 59 Hz.

[0142] The input to intracranial stimulating electrode ICSE signalprocessor 239, referred to above as conditioned intracranial stimulatingelectrode (ICSE) signal path 84, connects to spike detector 89. Spikedetector 89 identifies action potentials in a manner similar to thatdescribed above with reference to spike detector 85. Intracranialstimulating electrode ICSE signal processor 239 performs a similar setof functions as intracranial recording electrode ICRE signal processor238 on a different set of sensory feedback signals. As noted above,spike detection techniques are well known to those skilled in the art.

[0143] Spike detector 89 passes waveforms to spike characterizer 90,which uses well known techniques to calculate parameters thancharacterize the behavior of the individual and groups of neurons, theactivity of which is sensed by intracranial stimulating electrode array37. As noted above with respect to spike characterizer 86, thischaracterization may include parameterization of spikes, bursts ofspikes, and overall neural activity patterns. Similarly, theparameterization may include calculation of spike frequencies, burstfrequencies, inter-spike intervals, amplitudes, peak-to-valley times,valley-to-peak times, spectral composition, positive phase amplitudes,negative phase amplitudes, and positive-negative phase differentialamplitudes. Such characterization of neural spikes is known to thoseskilled in the art of neurophysiology. Based on this parameterization,spike characterizer 90 discriminates individual spikes and burstsoriginating from different neurons. As noted, such discriminationfacilitates serial monitoring of activity of individual and groups ofneurons and the assessment and quantification of activity change,reflective of change in disease state and of response to therapy.

[0144] Spike analyzer 91 receives the parameters from spikecharacterizer 90, and extracts higher level information, includingaverage spike frequencies, average interspike intervals, averageamplitudes, standard deviations thereof, trends, and temporalpatterning. The function and operation of spike analyzer 91 is similarto that described herein with reference to spike analyzer 87. Similarly,spike analyzer 91 may receive additional input directly or indirectlyfrom accelerometers and/or EMG arrays to facilitate the characterizationof neuronal firing patterns relative to activity of muscle groups andmovement of joints. This may include, for example, characterization ofneuronal spike amplitudes and tuning of firing to movement, includingbut not limited to movement velocity and direction. Suchcharacterization may be used to asses functioning of the sensorimotorsystem, including but not limited to motor response time, and to measurethe disease state and response to therapy.

[0145] Intracranial stimulating electrode (ICSE) single unit-based (SU)disease state estimator 92 receives input from either or both spikecharacterizer 90 and spike analyzer 91. ICSE SU disease state estimator92 receives input representative of the current neuronal activity fromspike characterizer 90. ICSE SU disease state estimator 92 may receiveinput representative of at least one of several signals, includingdesired neuronal activity, actual neuronal activity, and the differencebetween these quantities. The ICSE SU disease state estimate, calculatedby ICSE SU disease state estimator 92, may be comprised of a single or aplurality of signals, consistent with a representation of the diseasestate by a single or a multitude of state variables, respectively.

[0146] As with intracranial recording electrode signal processor 238,inputs and outputs from spike detector 89, spike characterizer 90, spikeanalyzer 91, disease state estimator 92, filter 106, spectral energycharacterizer 107, spectral energy analyzer 108, and disease stateestimator 109 may include individual or a plurality of signals, and eachmay have different parameters and signal processing characteristics foreach of the multiple signals processed. Because baseline neuronal firingrates differ among various anatomical and functional regions of thebrain, and their involvement in disease states and susceptibility tochange in firing patters varies, the respective signal processingcircuitry and logic varies correspondingly.

[0147]FIG. 4 is a schematic diagram of a globus pallidus 119 implantedwith stimulating and recording electrodes. Intracranial catheter 7 isshown in place with electrode of the intracranial stimulating electrodearray 37 located within the globus pallidus internus (Gpi) 120,including globus pallidus internus internal segment (GPi,i) 94 andglobus pallidus internus external segment (GPi,e) 95, and globuspallidus externus (GPe) 96.

[0148] Intracranial stimulating electrodes 1 and 2 are shown implantedin the globus pallidus internus internal segment (GPi,i) 94; andintracranial stimulating electrodes 3 and 4 are shown implanted in theglobus pallidus internus external segment (GPi,e) 95 and globus pallidusexternus (GPe) 96, respectively. It should be understood that thisarrangement is illustrative of one preferred embodiment, and otherstimulating and recording electrode configurations may be employedwithout departing from the present invention.

[0149] The optic tract 97 is shown in its close anatomical relationshipto the globus pallidus internus (Gpi) 120. The risk inherent intreatment modalities involving irreversible tissue ablation should beapparent; stereotactic errors of only one to several millimeters duringlesioning of the globus pallidus internus (Gpi) 12o may result inirreversible damage or complete destruction of the optic tract 97.Furthermore, the advantage of a system which dynamically adjusts theamplitude of inhibitory electrical stimulus to the globus pallidus 119to minimize said amplitude offers the potential advantage ofminimization of side effects including interference with visual signalsof the optic tract 97 and prevention of overtreatment.

[0150] Intracranial stimulating electrodes 1, 2, 3, 4 are shownimplanted in the GPi,i 94, GPi,e 95, GPe 96, respectively. This is onepreferred embodiment. Numerous permutations of electrode stimulationsite configuration may be employed, including more or fewer electrodesin each of these said regions, without departing from the presentinvention. Electrodes may be implanted within or adjacent to otherregions in addition to or instead of those listed above withoutdeparting from the present invention, said other reasons including butnot limited to the ventral medial Vim thalamic nucleus, other portion ofthe thalamus, subthalamic nucleus (STN), caudate, putamen, other basalganglia components, cingulate gyrus, other subcortical nuclei, nucleuslocus ceruleus, pedunculopontine nuclei of the reticular formation, rednucleus, substantia nigra, other brainstem structure, cerebellum,internal capsule, external capsule, corticospinal tract, pyramidaltract, ansa lenticularis, white matter tracts, motor cortex, premotorcortex, supplementary motor cortex, other motor cortical regions,somatosensory cortex, other sensory cortical regions, Broca's area,Wernickie's area, other cortical regions, other central nervous systemstructure, other peripheral nervous system structure, other neuralstructure, sensory organs, muscle tissue, or other non-neural structure.

[0151] Referring to FIGS. 3 and 4, a small percentage of cells in theglobus pallidus internus internal segment 94 and globus pallidusinternus external segment 95 exhibit tremor-synchronous discharges. Asnoted, at least one of single unit recordings from individual cells andmultiple unit recordings from a plurality of cells are processed bysignal processor 71. The single and multiple unit recordings may bederived from signals arising from intracranial stimulating electrodearray 37, intracranial recording electrode array 38, or other sources.The output from signal processor 71 is connected to control circuit 72and the output may represent at least one of disease state, magnitude ofsymptomatology, response to therapy, other parameter, and combinationthereof.

[0152] Individual electrodes comprising intracranial stimulatingelectrode array 37 and intracranial recording electrode array 38 mayeach be of the microelectrode type for single unit recordings,macroelectrode type for multiple unit recordings, other electrode type,or a combination thereof, without departing from the spirit of thepresent invention. In one preferred embodiment, intracranial stimulatingelectrode array 37 consists of macroelectrodes. The macroelectrodesfacilitate delivery of stimulation current at a lower charge density(coulombs per unit of electrode surface area) than microelectrodes ofthe same chemistry and surface treatment. The dimensions of intracranialstimulating electrodes 1-4 are selected such that the current density,or electrical current divided by electrode surface area, is below thethreshold of reversible charge injection for the given electrodematerial.

[0153] Standard single cell recording technique, using an electrode withan impedance of typically 1-2 Megohms, involves bandpass filtering with−6 decibel (dB) points at 300 and 10,000 Hertz. This filtering, or amodification thereof, may be accomplished by ICRE filter 65 and ICSEfilter 64; alternatively, it may be performed in spike detector 85 andspike detector 89, respectively, or other portion of stimulating andrecording circuit 26.

[0154]FIG. 5 is a block diagram of one embodiment of an EMG signalprocessor 233 which is included in a preferred embodiment of signalprocessor 71. EMG signal processor 233 processes signals from EMGelectrode array 50, performing functions including but not limited tofull wave rectification, envelope determination, bandpass filtering,threshold discrimination, and others described in more detail below, toproduce signals indicative of the overall magnitude of tremor as well asthe frequency at which tremor episodes occur. As noted, EMG electrodearray 50 includes, but is not limited to, proximal EMG electrode array45, enclosure-mounted EMG electrode array 46, and distal EMG electrodearray 47. EMG electrodes may be located in any implanted or externallocation without departing from the present invention. For example,electrodes may be located within or in proximity to the hand, forearm,arm foot, calf, leg, abdomen, torso, neck, head, haw, lip, eyelid,larynx, vocal cords, and tongue.

[0155] Conditioned EMG signal path 78 is also connected to a well-knownfull wave rectifier 123 now or later developed. Output from the fullwave rectifier 123 is coupled to an input of an envelope determiner 124.Determination of the envelope of a modulated signal is well known tothose skilled in the art of electronics; this may be readily implementedin analog or digital hardware or in software. Output of envelopedeterminer 124 is connected to inputs of filters 125, 127, 129, 131 and133. In one embodiment, filters 125, 127, 129, 131, 133 implementpassbands of approximately 0.1-2 Hz, 2-3 Hz, 3-5 Hz, 7-8 Hz, and 8-13Hz, respectively. Outputs of filters 125, 127, 129, 131 and 133 areconnected to threshold discriminators 126, 128, 130, 132, 134,respectively.

[0156] Threshold discriminators 126, 128, 130, 132, and 134 generateoutputs representing episodes of normal voluntary movement (Mv), lowfrequency intention tremor (Til) resting tremor (Tr), high frequencyintention tremor (Tih), and physiologic tremor (Tp), respectively. Theseoutputs are each connected to both of integrator 135 and counter 136.Integrator 135 generates outputs representative of the total activity ofeach of the above types of movement over at least one period of time.One such time period may be, for example, time since implantation, timesince last visit to physician or health care provider, month internal,week interval, day interval, interval since last medication dose,interval since last change in stimulation parameters, weighted averageof multiple time windows, and convolution of said activity witharbitrary time window function.

[0157] Counter 136 generates outputs representative of the number ofepisodes of each of the above types of movement over at least one periodof time. Such period of time may be, for example, time sinceimplantation, time since last visit to physician or health careprovider, month interval, week internal, day interval, interval sincelast medication dose, interval since last change in stimulationparameters, and weighted average of said number of episodes overmultiple time windows. Outputs from integrator 135 and counter 136 areconnect to EMG analyzer 137. EMG analyzer 137 performs a number offunctions including, for example, calculation of proportions of tremoractivity which are of the rest and the intention type, ratios ofdifferent types of tremor activity, the level of suppression of restingtremor activity with voluntary movement, assessment of temporal patternsof EMG activity. EMG disease state estimator 138 receives inputs fromEMG analyzer 137 and generates output representative of disease statebased upon said input. In one preferred embodiment, two disease statesare calculated, including a signal representative of the overallmagnitude of tremor activity and a signal representative of thefrequency of occurrence of tremor events. It should be understood thatall signals paths may transmit one or more signals without departingfrom the present invention.

[0158] EMG signals may be sensed from any individual or group of musclesand processed in a manner including but not limited to the determinationof severity and frequency of occurrence of various tremor types. Normalor physiologic tremor includes movement in the 8-13 Hz range and may beused as a normalization for the other types of sensed tremor. Thepredominant pathological form of tremor exhibited in Parkinson's diseasepatients is the classical “resting” tremor which includes movements inthe 3-5 Hz range which are present at rest and suppressed in thepresence of voluntary movement. In the present invention, quantificationof this tremor type serves as a heavily weighted sensory input in theassessment of disease state and response to therapy. Parkinson's diseasepatients may also exhibit intention tremor, of which there are twotypes. The first type of intention tremor is referred to as “lowfrequency intention tremor” (Til in the present invention) and consistsof movements in the 2-3 Hz range. A second type of intention tremor isreferred to as “high frequency intention tremor” Tih in the presentinvention and consists of irregular movements in the 7-8 Hz range whichpersist throughout voluntary movement. Other types of tremor havingassociated movement in other ranges may be sensed and represented by theEMG signals.

[0159] EMG signals from at least one of orbicularis oculi (effecting eyeclosure), levator palpebrae (effecting eye opening), and other musclescontributing to eyelid movement, may be sensed and processed todetermine frequency of eye blinking. Patients with Parkinson's diseaseexhibit a reduction in eye blinking frequency from the normal of 20 perminute to 5 to 10 per minute, and this parameter is sensed as a measureof disease severity and response to treatment. Additionally, said EMGsignals may be sensed and processed for detection and quantification ofblepharoclonus, or rhythmic fluttering of the eyelids, and used as ameasure of disease state and response to therapy. EMG signals, includingbaseline levels thereof, may be used to quantify rigidity and hypertonusas measures of disease state and response to therapy. Discharge patternsof individual motor units, including but not limited to synchronizationof multiple units and distribution of intervals preceding and followingdischarge, may be used as measures of disease state and response totherapy.

[0160]FIG. 6 is a block diagram of one embodiment of an EEG signalprocessor module 234 which is included in embodiments of signalprocessor 71. The EEG signal processor module 234 processes signals fromEEG electrode array 51. Conditioned EEG signal path 79 connects to aninput of artifact rejecter 139 which rejects signals with amplitudesabove a threshold. In one embodiment, this threshold is 0.1 mV. Anoutput from artifact rejecter 139 connects to an input of each ofsupplementary motor area signal extractor 140 and filters 143, 146, 149,152, 219. Filters 143, 146, 149, 152, and 219 are preferably of thebandpass type with passbands of 13-30 Hz, 8-13 Hz, 4-7 Hz, 0.1-4 Hz, and0.1-0.3 Hz, respectively. Each filter output is connected to an input ofan associated full wave rectifier 141, 144, 147, 150, 153, 220. Eachfull wave rectifier 141, 144, 147, 150, 153, 220 is connected to aninput of an associated envelope determiner 142, 145, 148, 151, 154, and221, respectively. The envelope determiners generate a signalrepresentative of the envelope of the input signal, typically performedby lowpass filtering with a time constant of 5 seconds. Finally, outputsof envelope determiners 142, 145, 148, 151, 154, and 221 are connectedto EEG disease state estimator 155.

[0161] Signal SMA generated by supplementary motor area signal extractor140 represents activity in the supplementary motor area ipsilateral tothe intracranial stimulating electrode array (ISEA) 37. Supplementarymotor area signal extractor 140 amplifies signals which are unique toelements of the EEG electrode array 51 which overlie the supplementarymotor area. The supplementary motor area receives neural signals vianeural projections from the basal ganglia and exhibits decreasedactivity in patients with Parkinson disease. The SMA is essential forsequential movements, which are often impaired in Parkinson's diseasepatients. The SMA signal provides a quantitative measure of diseasestate and response to therapy. The SMA signal is extracted from theanterior EEG leads, predominantly from those in the vicinity of thefrontal cortex, and provides a quantitative measure of disease state andresponse to therapy. Signals beta, alpha, theta, and delta consist of13-30 Hz, 8-13 Hz, 4-7 Hz, and 0.1-4 Hz activity, respectively.

[0162] Signal “resp” consists of 0.1-0.3 Hz activity and reflectsrespiration. Parkinson's disease patients exhibit irregular respiratorypatterns characterized by pauses and by abnormally deep breathing whileat rest and preceding speech. Assessment of respiratory irregularity aswell as other parameters derived from such resp signal serve asquantitative measures of disease state and response to therapy.

[0163] Anterior EEG electrodes are also used to sense EMG signals, andthe EMG signals are processed to determine activity of muscles includingbut not limited to those related to eye blinking activity. Processing ofthe EMG signals is included in the FIG. 6 circuit block diagram whichcontains the EEG signal processing component of signal processor 71.However, the processing could be incorporated into EMG signal processingcomponent of signal processor 71 without departing from scope of thepresent invention. Conditioned EEG signal path 79 is additionallyconnected to input of full wave rectifier 222, the output of which isconnected to the input of an envelope determiner 223. Envelopedeterminer 223 includes an output connected to input of filter 224.Filter 224 is preferably of the bandpass type with a passband range of0.1 to 20 Hz. Filter 224 has an output connected to input of thresholddiscriminator 225, the output of which is connected to EEG disease stateestimator 155.

[0164] Preferably, EMG signals arising from activity of at least one oforbicularis oculi (effecting eye closure), levator palpebrae (effectingeye opening), and other muscles the activity of which is associated witheyelid movement are sensed by anterior EEG electrodes. These EMG signalsare processed to determine eye blink events, and the rates andregularity of eye blinking activity are calculated. Frequency andirregularity of eyeblinking as well as blepharoclonus, or rhythmicfluttering of the eyelids, are quantified as measures of disease stateand response to therapy.

[0165]FIG. 7 is a block diagram of one embodiment of all accelerometersignal processor 235 which is incorporated into certain embodiments ofsignal processor 71. The accelerometer signal processor 235 processessignals from accelerometer array 52. Conditioned accelerometer signalpath 80 is connected to an input of each of a plurality of filters 156,160, 164, 168, 172. The filters are preferably of the bandpass type withpassbands of 0.1-2 Hz, 2-3 Hz, 3-5 Hz, 7-8 Hz, and 8-13 Hz,respectively. Other passband frequency ranges may also be used. Theoutput of each filter 156, 160, 164, 168, 172 is connected to anassociated full wave rectifiers 157, 161, 165, 169, and 173,respectively. The output of each rectifier 157, 161, 165, 169, and 173is connected to an associated envelope determiners 158, 162, 166, 170,and 174, respectively. Outputs of envelope determiners 158, 162, 166,170, and 174 are connected to inputs of an associated thresholddiscriminators 159, 163, 167, 171, and 175, respectively.

[0166] Outputs of threshold discriminators 159, 163, 167, 171, 175represent episodes of normal voluntary movement (Mv), low frequencyintention tremor (Til), resting tremor (Tr), high frequency intentiontremor (Tih), and physiologic tremor (Tp), respectively. These outputsare each connected to an integrator 176 and a counter 177. Integrator176 generates outputs representative of the total activity of each ofthe above types of movement over at least one period of time. As noted,such a time period may be, for example, time since implementation, timesince last visit to physician or health care provider, or some othertime interval, weighted average of multiple time windows, or convolutionof selected activities with an arbitrary time window function.

[0167] Counter 177 generates outputs representative of the number ofepisodes of each of the above types of movements over at least one suchperiod of time. Outputs from integrator 176 and counter 177 are connectto an acceleration analyzer 178. Acceleration analyzer 178 calculatesproportions of tremor types, such as the rest and intention types,ratios of different types of tremor activity, the level of suppressionof resting tremor activity with voluntary movement, and assessment oftemporal patterns of movement and acceleration. Acceleration analyzer178 may perform some or all of these calculations, as well as othercalculations, on alternative embodiments of the present invention.Acceleration-based disease state estimator 179 receives input fromacceleration analyzer 178 and generates output representative of diseasestate based upon such input.

[0168] It should be understood that accelerometer signals may be sensedfrom any individual or group of body components. For example, suchsignals may be sensed from joints, bones, and muscles. Furthermore, suchsignals may be processed in any well known manner, including thedetermination of severity and frequency of occurrence of various tremortypes. The types of tremor have been described above with respect toFIG. 5.

[0169]FIG. 8 is a block diagram of one embodiment of an acoustic signalprocessor 236 which is included in certain embodiments of signalprocessor 71. Acoustic signal processor 236 processes signals fromacoustic transducer array 53. Conditioned acoustic signal path 81 isconnected to a full wave rectifier 180 and a spectral analyzer 185. Theoutput of full wave rectifier 180 is connected to an input of anenvelope determiner 181, an output of which is connected to an input ofa low threshold discriminator 182 and a high threshold discriminator183. Low threshold discriminator 182 and high threshold discriminator183 each have an output connected to an input of timer 184. Timer 184generates an output signal representing latency (Lat) and is connectedto acoustic analyzer 186. An output of acoustic analyzer 186 isconnected to an input of acoustic-based disease state estimator 187.Latency (Lat) represents the latency between initiation of vocalutterance and the subsequent achievement of a threshold level of vocalamplitude. Such a vocal amplitude level is set by high thresholddiscriminator 183 and may represent steady state vocal amplitude or apreset or dynamically varying threshold. Latency from voice onset toachievement of steady state volume may be delayed in patients withParkinson's disease and is calculated as a measure of disease state andresponse to therapy.

[0170] Acoustic analyzer 186 receives input from spectral analyzer 185.The respiratory pattern is determined from rhythmic modulation of voiceand breathing sounds, sensed by elements of the acoustic transducerarray 53. Irregularity and pauses in respiration as well as abnormallydeep breathing patterns at rest and preceding speech are exhibited inParkinson's disease patients. Such parameters are quantified and used asestimates of disease state and response to therapy. Respirationdurations are quantified; abnormally deep respiration both during restand preceding speech are identified and used as indicators of diseasestate and response to therapy. Pauses in speech and decline in speechamplitude, or fading, are additionally monitored as indicators ofdisease state and response to therapy. Spectral composition of speech ismonitored and the change in spectral composition, reflective of changesof pharyngeal and laryngeal geometry, are quantified. Additionally, thefundamental vocal frequency; that is, the frequency at which theepiglottis vibrates, is extracted an that standard deviation of thefundamental vocal frequency is calculated over various time intervals asa quantified measure of the monotonic quality of speech characteristicof Parkinson's disease. This serves as yet another indicator of diseasestate and response to therapy.

[0171]FIG. 9 is block diagram of one embodiment of a peripheral nerveelectrode (PNE) signal processor 237 which is implemented in certainembodiments of signal processor 71. PNE signal processor 237 processessignals from peripheral nerve electrode array 54. These signals providedby peripheral nerve electrode array 54 are provided to PNE signalprocessor 237 via conditioned PNE signal path 82. Conditioned PNE signalpath 82 is connected to an input of a spike detector 188 and a filter191.

[0172] Spike detector 188 identifies action potentials. As noted, spikedetection techniques are well known to those skilled in the art, andgenerally employ low and high amplitude thresholds. Waveforms withamplitudes greater than the low threshold and lower than the highthreshold are determined to be action potentials. These thresholds maybe adjusted in real-time, and the low amplitude threshold is set abovethe amplitude of background noise and that of nearby cells not ofinterest, and the high amplitude threshold is set above the amplitude ofthe desired action potentials to allow their passage while eliminatinghigher amplitude noise spikes, such as artifacts arising from electricalstimulation currents. It should be understood that bandpass, notch, andother filtering techniques may also used to improve signal to noiseratio and the sensitivity and specific of spike detectors. Individualneuron action potentials are usually recorded using fine pointhigh-impedance electrodes, with impedances typically ranging from 1 to 5megohms. Alternatively, larger lower-impedance electrodes may be usedfor recording, in which case the signals obtained typically representaggregate activity of populations of neurons rather than actionpotentials from individual neurons. As noted above, peripheral nerveelectrode array 54 may include such electrodes as single unit recordingmicroelectrodes, multiple unit recording microelectrodes,intrafascicular electrodes, other intraneural electrodes, epineuralelectrodes, and any combination thereof.

[0173] A spike characterizer 189 determines firing patterns ofindividual neurons, including, for example, tonic activity, episodicactivity and burst firing. Spike characterizer 189 receives the signalspassed by spike detector 188 and calculates parameters that characterizethe behavior of the individual and groups of neurons, the activity ofwhich is sensed by peripheral nerve electrode array 54. Suchcharacterization includes but is not limited to parameterization ofspikes, bursts of spikes, and overall neural activity patterns.Parameterization includes but is not limited to calculation offrequencies of spikes, frequencies of bursts of spikes, inter-spikeintervals, spike amplitudes, peak-to-valley times, valley-to-peak times,spectral composition, positive phase amplitudes, negative phaseamplitudes, and positive-negative phase differential amplitudes. Theseparameters are described in further detail below with reference to FIG.14. Based on this parameterization, spike characterizer 189discriminates individual spikes and bursts originating from differentneurons. The discrimination facilitates aerial monitoring of activity ofindividual and groups of neurons and the assessment and quantificationof activity change, reflective of change in disease state and ofresponse to therapy.

[0174] A spike analyzer 190 receives as input the parameters from spikecharacterizer 189, and extracts higher level information, including butnot limited to average spike frequencies, average frequencies o burstsof spikes, average interspike intervals, average spike amplitudes,standard deviations thereof, trends, and temporal patterning.

[0175] Preferably, spike analyzer 190 additionally calculates the ratesof change of spike parameters. From prior and current rates of change,future behaviors may be predicted. Rates of change of the parametersinclude but are not limited to first, second, and third timederivatives. In alternative embodiments, spike analyzer 190 additionallycalculates weighted combinations of spike characteristics and performsconvolutions of spike waveforms with other spike waveforms, and otherpreset and varying waveforms. Such operations may be performed, forexample, for purposes including but not limited to autocorrelation anddigital filtering.

[0176] Spike analyzer 190 may receive additional input fromaccelerometers, such as those described above, including head mountedaccelerometer 12, proximal accelerometer 28, enclosure mountedaccelerometer 36, and distal accelerometer 33. Spike analyzer 190 mayreceive indirect input from these or other accelerometers, as well asfrom conditioned or processed signals arising therefrom. Suchconditioned or processed signals include, for example, the signaltransmitted by conditioned accelerometer signal path 80 (FIG. 7).

[0177] Spike analyzer 190 may receive additional input from EMG arrays.As noted, such EMG arrays may include, for example, proximal EMGelectrode array 45, enclosure-mounted EMG electrode array 46, and distalEMG electrode array 47. Spike analyzer 190 may also receive indirectinput from these or other EMG electrode arrays, as well as fromconditioned or processed signals arising therefrom. Such conditioned orprocessed signals include but are not limited to the signal transmittedby conditioned EMG signal path 78 (FIG. 5). These additional inputs fromaccelerometers and EMG arrays facilitates the characterization ofneuronal firing patterns relative to activity of muscle groups andmovement of joints. Such characterization may include, for example,characterization of neuronal spike amplitudes and tuning of neuronalspike frequencies to movement, including but not limited to the signaltransmitted by conditioned EMG signal path 78.

[0178] The additional input from accelerometers and EMG arrays alsofacilitates the characterization of neuronal firing patterns relative toactivity of muscle groups and movement of joints, including but notlimited to characterization of neuronal spike amplitudes and tuning ofneuronal spike frequencies to movement, including but not limited tomovement velocity and direction. These characterizations may be used toassess functioning of the sensorimotor system, including but not limitedto motor response time, and to measure the disease state and response totherapy.

[0179] Peripheral nerve electrode (PNE)-based single unit (SU) diseasestate estimator 194 receives an input representative of the currentneuronal activity from spike characterizer 189. PNE-based single unitdisease state estimator 194 may receive input representative of at leastone of several signals, including desired neuronal activity, actualneuronal activity, and the difference between these quantities. Theoutput from estimator 194 may carry a single or a plurality of signals,consistent with a representation of the disease state by a single or amultitude of state variables, respectively.

[0180] Filter 191 has an output connected to an input of spectral energycharacterizer 192. Spectral energy characterizer 192 calculates thespectral composition of the signals sensed by the peripheral nerveelectrode array 54. Spectral energy characterizer 192 provides outputsto each of spectral energy analyzer 193 and peripheral nerve electrode(PNE)-based multiple unit disease state estimator 232. Output ofspectral energy analyzer 193 is connected to an input of PNE-basedmultiple unit (MU) disease state estimator 232. PNE SU disease stateestimator 194 both receives input from and provides output to PNE MUdisease state estimator 232.

[0181] PNE MU disease state estimator 232 receives as an input signalsrepresentative of the current neuronal activity from spectral energycharacterizer 192. PNE MU disease state estimator 232 may receive inputrepresentative of at least one of several signals, including desiredneuronal activity, actual neuronal activity, and the difference betweenthese quantities. The output from PNE MU disease state estimator 232 maycarry a single or a plurality of signals, consistent with arepresentation of the disease state by a single or a multitude of statevariables, respectively.

[0182] It should be understood that inputs and outputs from each spikedetector 188, spike characterizer 189, spike analyzer 190, filter 191,spectral energy characterizer 192, spectral energy analyzer 193, andPNE-based single unit disease state estimator 194, and PNE-basedmultiple unit disease state estimator 232 may each be comprised ofindividual signals or a plurality of signals. It should also beunderstood that each of these the units, spike detector 188, spikecharacterizer 189, spike analyzer 190, filter 191, spectral energycharacterizer 192, spectral energy analyzer 193, and PNE-based singleunit disease state estimator 194, and PNE MU disease state estimator 232may each have different parameters and signal processing characteristicsfor each of the multiple signals processed. Modifications of thisprocessing circuitry may be made to accommodate various combinations ofintraneural electrodes, used for single and multiple unit recordings,and epineural electrodes, used for compound action potential recordings,without departing from the present invention.

[0183]FIG. 11 is a schematic diagram of one embodiment of apatient-neural modulator system 999 illustrated in FIG. 2 with feedbackcontrol. Patient-neural modulator system 999 primarily includes anobserver 228 and a controller 229. An observer is a component of acontrol system that is known to those or ordinary skill in the art ofcontrol systems. An observer is a functional block in which variables,typically represented in software as parameter values or in hardware aselectrical signal amplitudes, represent states of the controlled system.Such a component is used in controlling systems in which one or more ofthe state variables are not directly observable from the sensed signals.An observer essentially includes a simulated version of the controlledsystem. Its input are the same control law output signals delivered tothe controlled system, and its outputs are desired to match those sensedoutputs of the controlled system. The difference between the outputs ofthe observer and the measured outputs of the controlled system, that is,the outputs of a motor control portion of the patient's nervous systemin this case, ale used to calculate an observer error signal which maythen be used to correct the observer error. Since the observer isimplemented in software or hardware, all of its signals, including allstate variables, are accessible. In a system such as the complex neuralcircuitry of the patient, one or more of the state variables may not be“observable”, that is directly measurable or calculatable based onmeasured values. In such a case, the state variables present in theobserver may be used as “estimates” of the actual state variables andincluded in the control law. The general use of “observers” forestimation of “unobservable” state variables is known to those skilledin the art of control theory. The use of observers for the estimation ofneural state variables, disease states, and responses to therapy is oneof the teachings of the present invention.

[0184] Observer 228 includes signal conditioning circuit 76 (FIG. 2) andsignal processor 71 (FIGS. 2, 10). Signal processor 71, as noted,includes disease state estimator module array (DSEMA) 229 and aggregatedisease state estimator 195. Observer 228 receives patient output “y”from patient 227. Patient output “y” is comprised of one or more signalsarising from patient 227. In one preferred embodiment patient output “y”includes one or more signals from EMG electrode array 50, EEG electrodearray 51, accelerometer array 52, acoustic transducer array 53,peripheral nerve electrode array 54, intracranial recording electrodearray 38, and intracranial stimulating electrode array 37. It should beunderstood that additional signals f the same or different type may alsobe included.

[0185] Control circuit 72 (FIG. 2) includes summator 226 which receivesan input from reference module 116, and a control law circuit block 231.Controller 229 includes the control law circuit lock 231 and outputstage circuit 77. Controller 229 generates a neural modulation waveforms“u”, described in detail below with reference to FIG. 13. The functionand operation of each of these modules is described in detail below.

[0186] Reference disease state “r”, generated by reference module 116,is a non-inverting input to summator 226, providing disease state andtarget reference values for the single or plurality of control lawsimplemented in control law circuit block 231 introduced above withreference to FIG. 2. Reference module 116 may also receive input fromcontrol circuit 72, facilitating the dynamic adjustment of referencevalues. Reference disease state “r” may comprise a single or pluralityof signals, each of which may be zero, constant, or time-varyingindependent of the other. Disease state error “e” is output fromsummator 226 and input to controller 229. Disease state error “e”, whichmay comprise a single or plurality of signals, represents a differencebetween a desired disease state (represented by reference disease state“r”) and an actual disease state (represented by disease state estimate“x”). Other methods of calculating disease state estimate “x”, includingbut not limited to linear or nonlinear combinations of reference diseasestate “r” and disease state estimate “x”, may be employed withoutdeparting from the present invention. Controller 229 is comprised ofcontrol law circuit block 231 and output stage circuit 77.

[0187] Disease state error “e” is input to control law circuit block 231which generates a control circuit output “uc.” Control law circuit block231 is connected to an input of output stage circuit 77. The output ofthe controller 229, which is generated by the output stage circuit 77,“u”, is delivered to patient 227 in the form of neural modulationwaveforms, described in detail below with reference to FIG. 13.

[0188] Patient output “y” is input to signal conditioning circuit 76,the output of which is connected to the input of DSEMA 229. The outputof DSEMA 229 is provided to an aggregate disease state estimator 195,the output of which is the disease state estimate x. Disease stateestimate x, which may be comprised of a single or plurality of signals,is an inverting input to summator 226.

[0189] Control law circuit block 231 receives disease state estimate xas an additional input, for use in nonlinear, adaptive and other controllaws. Reference module 116 receives input from DSEMA 229 and aggregatedisease state estimator 195 for use in dynamically determining referencedisease state r. Other modifications, including substitutions,additions, and deletions, may be made to the control loop withoutdeparting from the present invention.

[0190] Control law circuit block 231 has an autocalibration mode inwhich multivariable sweeps through stimulation parameters andstimulating electrode configurations are performed to automate andexpedite parameter and configuration optimization. This autocalibrationfeature enables rapid optimization of treatment, eliminating months ofiterations of trial and error in optimizing stimulation parameters andelectrode configuration necessitated by the prior technique of constantparameter stimulation. Additionally, this autocalibration featurepermits real-time adjustment and optimization of stimulation parametersand electrode configuration. This is particularly useful to overcomeincreases in electrode impedance which result from the body's normalresponse to implanted foreign bodies in which a fibrotic capsule iscommonly formed around the electrodes. Effects of shifts in electrodeposition relative to a target structures may be minimized by saidautocalibration feature. Detection of changes in electrode impedance andposition are facilitated by autocalibration feature. The autocalibrationfeature facilities detection of changes in electrode impedance andposition. Notification of patient and health care provider allowsproactive action, including automated or manual adjustment of treatmentparameters and advance knowledge of impending electrode replacementneeds.

[0191]FIG. 12 is a schematic diagram of control circuit 72. As noted,control circuit 72 comprises control laws circuit block 231 and summator226. Disease state error “e” is input to gain stages of control laws,including but not limited to at least one of proportional gain 197,differential gain 198, integral gain 199, nonlinear gain 200, adaptivegain 201, sliding gain 202, and model reference gain 203.

[0192] An output of each of these gain stages is connected to what isreferred to herein as control law stages. In the illustrativeembodiment, control law stages includes proportional controller 230,differential controller 204, integral controller 205, nonlinearcontroller 206, adaptive controller 207, sliding controller 208, andmodel reference controller 209, respectively.

[0193] Outputs of these control law stages are connected to weightstages, including proportional controller weight 210, differentialcontroller weight 211, integral controller weight 212, nonlinearcontroller weight 213, adaptive controller weight 214, slidingcontroller weight 215, and model reference controller weight 216.Outputs of the weight stages are noninverting inputs to summator 217,the output of which is control circuit output “uc”. The weight stagesmay be any combination of at least one of constant, time varying, andnonlinear without departing from the present invention.

[0194] Disease state estimate x is input to nonlinear controller 206,adaptive controller 207, sliding controller 208, and model referencecontroller 209. The control laws depicted are representative of onepossible implementation; numerous variations, including substitutions,additions, and deletions, may be made without departing from the presentinvention.

[0195] The present invention optimizes the efficiency of energy used inthe treatment given to the patient by minimizing to a satisfactory levelthe stimulation intensity to provide the level of treatment magnitudenecessary to control disease symptoms without extending additionalenergy delivering unnecessary overtreatment. In the definition of thecontrol law, a command input or reference input (denoted as r in FIGS.11 and 12) specifies the target disease state. In the preferredembodiment, r specifies the target amplitude of tremor. The control lawgenerates an electrical stimulation magnitude just sufficient to reducethe patient's tremor to the target value. With this apparatus andmethod, the precise amount of electrical energy required is delivered,and overstimulation is avoided. In present stimulation systems, aconstant level of stimulation is delivered, resulting in either of twoundesirable scenarios when disease state and symptoms fluctuate: (1)undertreatment, i.e. tremor amplitude exceeds desirable level or (2)overtreatment or excess stimulation, in which more electrical energy isdelivered than is actually needed. In the overtreatment case, batterylife is unnecessarily reduced. The energy delivered to the tissue in theform of a stimulation signal represents a substantial portion of theenergy consumed by the implanted device; minimization of this energysubstantially extends battery life, with a consequent extension of timein between reoperations to replace expended batteries.

[0196]FIG. 13 is a schematic diagram of electrical stimulation waveformsfor neural modulation. The illustrated ideal stimulus waveform is acharge balanced biphasic current controlled electrical pulse train. Twocycles of this waveform are depicted, each of which is made of a smallercathodic phase followed, after a short delay, by a larger anodic phase.In one preferred embodiment, a current controlled stimulus is delivered;and the “Stimulus Amplitude” represents stimulation current. A voltagecontrolled or other stimulus may be used without departing from thepresent invention. Similarly, other waveforms, including an anodic phasepreceding a cathodic phase, a monophasic pulse, a triphasic pulse, orthe waveform may be used without departing from the present invention.

[0197] The amplitude of the first phase, depicted here as cathodic, isgiven by pulse amplitude 1 PA1; the amplitude of the second phase,depicted here as anodic, is given by pulse amplitude 2 PA2. Thedurations of the first and second phases are pulse width 1 PW1 and pulsewidth 1 PW2, respectively. Phase 1 and phase 2 are separated by a briefdelay d. Waveforms repeat with a stimulation period T, defining thestimulation frequency as f=1/T.

[0198] The area under the curve for each phase represents the charge Qtransferred, and in the preferred embodiment, these quantities are equaland opposite for the cathodic (Q1) and anodic (Q2) pulses, i.e. Q=Q1=Q2.For rectangular pulses, the charge transferred per pulse is given byQ1=PA1*PW1 and Q2=PA2*PW2. The charge balancing constraint given by−Q1=Q2 imposes the relation PA1*PW1=−PA2*PW2. Departure from the chargebalancing constraint, as is desired for optimal function of certainelectrode materials, in included in the present invention.

[0199] The stimulus amplitudes PA1 and PA2, durations PW1 and PW2,frequency f, or a combination thereof may be varied to modulate theintensity of the said stimulus. A series of stimulus waveforms may bedelivered as a burst, in which case the number of stimuli per burst, thefrequency of waveforms within the said burst, the frequency at which thebursts are repeated, or a combination thereof may additionally be variedto modulate the stimulus intensity.

[0200] Typical values for stimulation parameters include f=100-300 Hz,PA1 and PA2 range from 10 microamps to 10 milliamps, PW1 and PW2 rangefrom 50 microseconds to 100 milliseconds. These values arerepresentative, and departure from these ranges is included in theapparatus and method of the present invention.

[0201]FIG. 14 is a schematic diagram of one example of the recordedwaveforms. This represents an individual action potential from a singlecell recording, typically recorded from intracranial microelectrodes.Aggregates of multiple such waveforms are recorded from largerintracranial electrodes. The action potentials may be characterizedaccording to a set of parameters including but not limited to time tovalley 1 TV1, time to peak 1 TP1, time to valley 2 TV2, amplitude ofvalley 1 AV1, amplitude of peak 1 AP1, amplutide of valley 2 AV2, andalgebraic combinations and polarity reversals thereof.

[0202] When recording activity from more than one cell, saidcharacterization facilitates discrimination of waveforms by individualrecorded cell. The discrimination allows activity of a plurality ofcells to be individually followed over time. The parameterization may beperformed separately on signals recorded from different electrodes.Alternatively, said parameterization may be performed on signals pooledfrom multiple electrodes.

[0203] Following is a description of a general form for representingdisease state.

[0204] Disease State DS is a vector of individual disease states,including intrinsic disease states DS1 and extrinsic disease states DSE:

DS=[DS ₁ DS _(E)]

[0205] Intrinsic disease states and extrinsic disease states are,themselves vectors of individual disease states:

DS ₁ =[DS ₁₁ DS ₁₂ DS ₁₃ . . . DS _(IN)]

DS _(E) =[DS _(E1) DS _(E2) DS _(E3) . . . DS _(EM)]

[0206] Intrinsic Disease States include those disease states whichcharacterize the state of disease at a given point in time. ExtrinsicDisease States include variations of intrinsic disease states, includingbut not limited to cyclical variations in Intrinsic Disease States,variations in Intrinsic Disease States which occur in response toexternal events, and variations in Intrinsic Disease States which occurin response to levels of and changes in levels of electricalstimulation. Said external events include but are not limited topharmacologic dosing, consumption of meals, awakening, falling asleep,transitioning from Parkinsonian “on” state to Parkinsonian “off” state,transitioning from Parkinsonian “off” state to Parkinsonian “on” state.

[0207] Each of Intrinsic Disease States and Extrinsic Disease Statesinclude but are not limited to those defined herein; additional diseasestates and definitions thereof may be added without departing from thepresent invention.

[0208] The first intrinsic disease state DS₁₁ represents the level ofresting tremor

DS₁₁—RT_(N)

[0209] Where Normalized Resting Tremor Magnitude RT_(N) is given by:

RT _(N) =T _(A,3-5) *W _(TA,3-5) +T _(E,3-5) *W _(TE,3-5) +T _(P,3-5) *W_(PF,3-5) +T _(C,3-5) +W _(IC,3-5) +T _(N,3-5) *W _(IN,3-5) +T _(S,3-5)*W _(IS,3-5) +T _(I,3-5) *W _(11,3-5)

[0210] Where the factors from which the Resting Tremor Magnitude RT_(N)is determined, representing estimates of the magnitude of 3-5 Hertzmovement of selected body segments, including but not limited to limbs,torso, and head are:

[0211] T_(A,3-5)=Tremor level determined by acceleration monitoring

[0212] W_(TA,3-5)=Weighting factor for tremor T_(A,3-5)

[0213] T_(E,3-5)=Tremor level determined by electromyographic (EMG)monitoring

[0214] W_(TE,3-5)=Weighting factor for tremor T_(E,3-5)

[0215] T_(P,3-5)=Tremor level determined by peripheral nerve electrodemonitoring

[0216] W_(TP,3-5)=Weighting factor for tremor T_(P,3-5)

[0217] T_(C,3-5)=Tremor level determined by cortical electrodemonitoring

[0218] W_(TC,3-5)=Weighting factor for tremor T_(C,3-5)

[0219] T_(N,3-5)=Tremor level determined by neural monitoring, includingsubcortical nuclei, white matter tracts, and spinal cord neurons

[0220] W_(TN,3-5)=Weighting factor for tremor T_(N,3-5)

[0221] T_(S,3-5)=Tremor level determined by acoustic sensor monitoring

[0222] W_(TS,3-5)=Weighting factor for tremor T_(S,3-5)

[0223] Weighting factors are adjusted after implantation to achievenormalization of RT_(N) and to allow for selective weighting of tremorlevels as determined from signals arising from various sensors,including but not limited to those listed.

[0224] These calculations may be implemented in analog hardware, digitalhardware, software, or other form. In the preferred embodiment, valuesare implemented as 16-bit variables; ranges for said weighting factorsand tremor levels are 0 to 65535. These ranges may be changed orimplemented in analog form without departing from the present invention.

[0225] The second intrinsic disease state DS₁₂ represents the level ofdyskinesia:

DS₁₂=D_(N)

[0226] Where Normalized Dyskinesia Magnitude D_(N) is given by:

D _(N) =D _(A) *W _(DA) +T _(F) *W _(FF) +T _(P) *W _(PF) +T _(C) +W_(IC) +T _(N) *W _(IN) +T _(S) *W _(IS) +T _(E) *W _(IF)

[0227] Where

[0228] D_(A,3-5)=Dyskinesia level determined by acceleration monitoring

[0229] W_(DA,3-5)=Weighting factor for Dyskinesia D_(A,3-5)

[0230] D_(E,3-5)=Dyskinesia level determined by electromyographic (EMG)monitoring

[0231] W_(DE,3-5)=Weighting factor for Dyskinesia D_(E,3-5)

[0232] D_(P,3-5)=Dyskinesia level determined by peripheral nerveelectrode monitoring

[0233] W_(DP,3-5)=Weighting factor for Dyskinesia D_(P,3-5)

[0234] D_(C,3-5)=Dyskinesia level determined by cortical electrodemonitoring

[0235] W_(DC,3-5)=Weighting factor for Dyskinesia D_(C,3-5)

[0236] D_(N,3-5)=Dyskinesia level determined by neural monitoring,including subcortical nuclei, white matter tracts, and spinal cordneurons

[0237] W_(DN,3-5)=Weighting factor for Dyskinesia D_(N,3-5)

[0238] D_(S,3-5)=Dyskinesia level determined by acoustic sensormonitoring

[0239] W_(DS,3-5)=Weighting factor for Dyskinesia D_(S,3-5)

[0240] The third intrinsic disease state DS₁₃ represents the level ofrigidity.

DS₁₃=R_(N)

[0241] Where Normalized Rigidity Magnitude R_(N) is given by:

R _(N) =R _(A) *W _(RA) +R _(E) *W _(RF) +R _(P) *W _(RE) +R _(C) +W_(RC) +R _(N) *W _(RN) +R _(S) *W _(RS) +R _(F) *W _(RF)

[0242] Where

[0243] R_(A,3-5)=Rigidity level determined by acceleration monitoring

[0244] W_(RA,3-5)=Weighting factor for Rigidity R_(A,3-5)

[0245] R_(E,3-5)=Rigidity level determined by electromyographic (EMG)monitoring

[0246] W_(RE,3-5)=Weighting factor for Rigidity R_(E,3-5)

[0247] R_(P,3-5)=Rigidity level determined by peripheral nerve electrodemonitoring

[0248] W_(RP,3-5)=Weighting factor for Rigidity R_(P,3-5)

[0249] R_(C,3-5)=Rigidity level determined by cortical electrodemonitoring

[0250] W_(RC,3-5)=Weighting factor for Rigidity R_(C,3-5)

[0251] R_(N,3-5)=Rigidity level determined by neural monitoring,including subcortical nuclei, white matter tracts, and spinal cordneurons

[0252] W_(RN,3-5)=Weighting factor for Rigidity R_(N,3-5)

[0253] R_(S,3-5)=Rigidity level determined by acoustic sensor monitoring

[0254] W_(RS,3-5)=Weighting factor for Rigidity R_(S,3-5)

[0255] The fourth intrinsic disease state DS₁₄ represents the level ofbradykinesia.

DS₁₄=B_(N)

[0256] Where Normalized Bradykinesia Magnitude B_(N) is given by:

B _(N) =B _(A) *W _(BA) +B _(F) *W _(BE) +B _(P) *W _(PF) +B _(C) +W_(BC) +B _(N) *W _(BN) +B _(S) *W _(BS) +B _(E) *W _(BF)

[0257] Where

[0258] R_(A)=Bradykinesia level determined by acceleration monitoring

[0259] W_(RA)=Weighting factor for Bradykinesia R_(A)

[0260] R_(E)=Bradykinesia level determined by electromyographic (EMG)monitoring

[0261] W_(RE)=Weighting factor for Bradykinesia R_(E)

[0262] R_(P)=Bradykinesia level determined by peripheral nerve electrodemonitoring

[0263] W_(RP)=Weighting factor for Bradykinesia R_(P)

[0264] R_(C)=Bradykinesia level determined by cortical electrodemonitoring

[0265] W_(RC)=Weighting factor for Bradykinesia R_(C)

[0266] R_(N)=Bradykinesia level determined by neural monitoring,including subcortical nuclei, white matter tracts, and spinal cordneurons

[0267] W_(RN)=Weighting factor for Bradykinesia R_(N)

[0268] R_(S)=Bradykinesia level determined by acoustic sensor monitoring

[0269] W_(RS)=Weighting factor for Bradykinesia R_(S)

[0270] The control law drives these disease states toward theirreference values, nominally 0, according to a vector of weights,establishing a prioritization

[0271] Side Effects:

[0272] Side effects and other parameters, such as power consumption andcurrent magnitude, are also quantified and minimized according to a costfunction.

[0273] One advantage of the present invention is that it providesprediction of future symptomatology, cognitive and neuromotorfunctionality, and treatment magnitude requirements. Such predictionsmay be based on preset, learned and real-time sensed parameters as wellas input from the patient, physician or other person or system. Theprediction of future symptomatology is based upon any of severalweighted combination of parameters. Based upon prior characterization ofthe circadian fluctuation in symptomatology (that is, tremor magnitudefor deep brain stimulation or level of depression for stimulation ofother sites including locus cerulius), future fluctuations may bepredicted. An estimate, or model, of fluctuation may be based upon acombination of preset, learned, and real-time sensed parameters. Presetparameters are derived from clinical studies designed specifically forthe purpose of gathering such data, or from estimates extracted fromdata gleaned from published literature. Real-time sensed parameters arederived from the current states (and changes, i.e. derivatives and otherprocessed signals, thereof) of sensed and processed signals. Learnedparameters are based upon the time histories of previously sensedsignals. For example, the circadian fluctuation in tremor amplitude maybe sensed; a weighted average of this data collected over numerous priordays provides as estimate of the expected tremor amplitude as well as astandard deviation and other statistical parameters to characterize theanticipated tremor amplitude. Similarly, in the presence of closed-loopfeedback, the level of stimulation required to reduce or eliminatetremor may be used as an estimate of the “amplitude” or state of theunderlying disease.

[0274] Another advantage of the present invention is that it performsautomated determination of the optimum magnitude of treatment—by sensingand quantifying the magnitude and frequency of tremor activity in thepatient, a quantitative representation of the level or “state” of thedisease is determined. The disease state is monitored as treatmentparameters are automatically varied, and the local or absolute minimumin disease state is achieved as the optimal set of stimulationparameters is converged upon. The disease state may be represented as asingle value or a vector or matrix of values; in the latter two cases, amultivariable optimization algorithm is employed with appropriateweighting factors.

[0275] Having now described several embodiments of the invention, itshould be apparent to those skilled in the art that the foregoing ismerely illustrative and not limiting, having been presented by way ofexample only. For example, all signal paths may transmit a single orplurality of signals without departing from the present invention.Numerous modifications and other embodiments are within the scope of oneof ordinary skill in the art and are contemplated as falling within thescope of the invention as defined by the appended claims.

What is claimed is:
 1. A neural modulation system for use in treatingdisease which provides stimulus intensity which may be varied.
 2. Thedevice of claim 1, wherein said stimulation is at least one ofactivating, inhibitory, and a combination of activating and inhibitory.3. The device of claim 1, wherein said disease is at least one ofneurologic and psychiatric.
 4. The device of claim 3, wherein saidneurologic disease includes at least one of Parkinson's disease,Huntington's disease, Parkinsonism, rigidity, hemiballism,choreoathetosis, dystonia, akinesia, bradykinesia, hyperkinesia, othermovement disorder, epilepsy, or the seizure disorder.
 5. The device ofclaim 4, wherein said psychiatric disease includes at least one ofdepression, bipolar disorder, other affective disorder, anxiety, phobia,schizophrenia, multiple personality disorder.
 6. The device of claim 3,wherein said psychiatric disorder includes substance abuse, attentiondeficit hyperactivity disorder, impaired control of aggression, orimpaired control of sexual behavior.
 7. The device of claim 1, whereinsaid stimulus intensity us time-varying.
 8. The device of claim 7,wherein said time-varying stimulus intensity is preprogrammed.
 9. Thedevice of claim 8, wherein said time-varying stimulus intensity variesas a function of time, including but not limited to time of day, timerelative to food intake, time of year, time since implantation, timesince system was reprogrammed, and time since system was evaluated. 10.The device of claim 1, wherein sensory feedback is used in thedetermination of said stimulus intensity.
 11. The device of claim 10,wherein said sensory feedback consists of at least one ofelectromyographic signals, accelerometers, electrodes, acoustictransducers, force sensors, pressure sensors, velocity sensors,neurotransmitter sensor, and chemical sensors.
 12. The device of claim11, wherein said sensory feedback electrodes may also function asstimulating electrodes.
 13. The device of claim 11, wherein said sensoryfeedback electrodes record signals from at least one of the globuspallidus internus, globus pallidus externus, internal capsule, thalamus,the subthalamic nucleus, the caudate, the putamen, the ansalenticularis, the corticospinal tract, the substantia nigra, thenigrostriatal tract, cerebral cortex, motor cortex, premotor cortex,sensory cortex, cerebellum, cerebellar cortex, cerebellar nuclei,cerebellar projections, the brain stem, the spinal cord, central nervoussystem, the cranial nerves the peripheral nervous system, peripheralnerves, ganglia, sensory organs, golgi tendons, muscle stretchreceptors, intrafusal fibers, and extrafusal fibers.
 14. The device ofclaim 11, wherein said accelerometer measures movement of at least oneof the head, eyes, face, jaw, neck, axial skeleton, appendicularskeleton, arms, legs, hands, feet, fingers, toes, vertebral column, andpelvis.
 15. The device of claim 11, wherein said electromyographicsignal arise from at least one of facial muscles, extraocular muscles,muscles of mastication, neck muscles, shoulder muscles, arm muscles,wrist muscles, hand muscles, torso muscles, chest muscles, abdominalmuscles, back muscles, buttock muscles, peroneal muscles, leg muscles,calf muscles, foot muscles, and visceral muscles.
 16. A device as setforth in claim 4, wherein a control law is used in the determination ofthe stimulus intensity as a function of input which is a combination ofat least one of sensory feedback signals, preprogrammed parameters, timeof day, recumbency, level of activity, adaptive parameters, estimates ofsystem performance, and user determined input
 17. The device as of claim16, wherein said user determined input includes at least one of magnetmovement over implanted sensor, muscle contraction, joint movement,audible input, switch activation, head position, head movement, shoulderposition, and shoulder movement.
 18. The device as of claim 16, whereinsaid control law is a combination of at least one of proportionalfunction, derivative function, integral function, nonlinear function,multivariable function, sliding function, model reference function,adaptive function, filter function, and time-varying function of saidinput.
 19. The device of claim 16, wherein said control law isproportional.
 20. The device of claim 16, wherein said control law is ofthe proportional-derivative type.
 21. The device of claim 16, whereinsaid control law is nonlinear.
 22. The device of claim 16, wherein saidcontrol law is multivariable.
 23. The device of claim 16, wherein saidcontrol law is sliding.
 24. The device of claim 16, wherein said controllaw is adaptive.
 25. The device of claim 16, wherein said control law ismodel reference.
 26. The device of claim 9, wherein sensory feedback isused to estimate mental state.
 27. The device of claim 26, wherein saidestimated psychiatric state includes at least one of: mood, elation,depression, anxiety level, and psychosis.
 28. A neurological controlsystem for modulating the activity of at least one nervous systemcomponent, the neurological control system comprising: at least oneintracranial stimulating electrode, each constructed and arranged todeliver a neural modulation signal to at least one nervous systemcomponent; at least one sensor, each constructed and arranged to senseat least one parameter, including but not limited to physiologic valuesand neural signals, which is indicative of at least one of diseasestate, magnitude of symptoms, and response to therapy; and a stimulatingand recording unit constructed and arranged to generate said neuralmodulation signal based upon a neural response sensed by said at leastone sensor in response to a previously delivered neural modulationsignal.
 29. The system of claim 28, wherein said particularcharacteristic is indicative of at least one of a neurological andpsychiatric condition.
 30. The system of claim 28, wherein saidstimulating and recording unit generates said neural modulation signalin accordance with predetermined treatment parameters to treat at leastone of a neurological and psychiatric disease.
 31. The system of claim28, wherein said stimulating and recording unit comprises: a signalprocessor constructed and arranged to determine neural system states;and a control module for adjusting said at least one neural modulationsignal based upon said neural system state.
 32. The system of claim 28,wherein each of said at least one sensor generates one or more neuralresponse signals, and wherein said stimulating and recording unitfurther comprises: a signal conditioner, interposed between said atleast one sensor and said signal processor, constructed and arranged tomodify said neural response signals appropriately for said signalprocessor.
 33. The system of claim 32, wherein said signal conditionercomprises: at least one amplifier, each constructed and arranged toamplify said neural response signals generated by an associated one ofsaid at least one sensor; and at least one signal filter, eachconstructed and arranged to filter said amplified neural responsesignals generated by an associated one of said at least one sensor andan associated at least one amplifier.
 34. The system of claim 33,wherein said at least one signal filter performs at least one of lowpassfiltering, highpass filtering, bandpass filtering and notch filtering ofsaid amplified neural response signal.
 35. An apparatus for modulatingthe activity of at least one nervous system component, said systemcomprising: means for delivering neural modulation signal to saidnervous system component; and means for sensing neural response to saidneural modulation signal.
 36. The apparatus of claim 35, wherein saiddelivery means comprises means for generating said neural modulationsignal, said generating means comprising: signal conditioning means forconditioning sensed neural response signals, said conditioning includingbut not limited to at least one of amplification, lowpass filtering,highpass filtering, bandpass filtering, notch filtering, root-meansquare calculation, envelope determination, and rectification; signalprocessing means for processing said conditioned sensed neural responsesignals to determine neural system states, including but not limited toa single or plurality or physiologic states and a single or plurality ofdisease states; and controller means for adjusting neural modulationsignal in response to sensed neural response to signal.
 37. Theapparatus of claim 36, wherein said activity is indicative of aneurologic and psychiatric disease.
 38. The apparatus of claim 36,wherein said disease state includes but is not limited to Parkinson'sdisease, Huntington's disease, hemiballism, choreoathetosis, dystonia,akinesia, bradykinesia, restless legs syndrome, other movement disorder,epilepsy, Alzheimer's disease, dementia, other neurologic disorder,depression, mania, bipolar disorder, other affective disorder, anxietydisorder, phobia disorder, borderline personality disorder,schizophrenia, multiple personality disorder, and other psychiatricdisorder.
 39. The apparatus of claim 38, wherein said disease is amovement disorder.
 40. The apparatus of claim 39, wherein said means fordelivering neural modulation signal to said nervous system componentincludes electrodes implemented into at least one of the globus pallidusinternus (GPi), including globus pallidus internus internal segment(GPi,i) and globus pallidus internus external segment (GPi,e), globuspallidus externus (GPe), ventral medial (Vim) thalamic nucleus, otherportion of the thalamus, subthalamic nucleus (STN), caudate, putamen,other basal ganglia components, cingulate gyrus, other subcorticalnuclei, nucleus locus ceruleus, pedunculopontine nuclei of the reticularformation, red nucleus, substantia nigra, other brainstem structure,cerebellum, internal capsule, external capsule, corticospinal tract,pyramidal tract, ansa lenticularis, white matter tracts, motor cortex,premotor cortex, supplementary motor cortex, other motor corticalregions, somatosensory cortex, other sensory cortical regions, Broca'sarea, Wernicke's area, other cortical regions, other central nervoussystem structure, other peripheral nervous system structure, otherneural structure, sensory organs, muscle tissue, or other non-neuralstructure.
 41. The apparatus of claim 39, wherein said means for sensingneural response includes but is not limited to at least one of measuresof disease state and response to therapy.
 42. The apparatus of claim 39,wherein said means for sensing neural response includes at least one ofaccelerometers electromyography electrodes, acoustic sensors,intracranial electrodes, electroencephalography electrodes, andperipheral nerve electrodes.
 43. The apparatus of claim 39, wherein saidmeans for sensing neural response includes a weighted aggregate ofprocessed signals derived from at least one of accelerometers,electromyography electrodes, acoustic sensors, intracranial electrodes,electroencephalography electrodes, and peripheral nerve electrodes. 44.The apparatus of claim 38, wherein said controller means for generatinga neural modulation signal employs a control law using as input signalsderived from at least one of accelerometers, electromyographyelectrodes, acoustic sensors, intracranial electrodes,electroencephalography electrodes, and peripheral nerve electrodes. 45.The apparatus of claim 40, wherein said controller means for generatinga neural modulation signal employs a control law using as input aweighted aggregate of processed signals derived from at least one ofaccelerometers, electromyography electrodes, acoustic sensors,intracranial electrodes, electroencephalography electrodes, andperipheral nerve electrodes.